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Posts Tagged ‘genetic epidemiology’

The University of Bristol News webpage on the 16th of August 2016. I feel privileged to have had the chance to be the face of the university in an important announcement such as this.

The University of Bristol News webpage on the 16th of August 2016. I feel privileged to have had the chance to be the face of the university in an important announcement such as this.

The University of Bristol has been ranked as 8th in the UK and has risen nine places to 57th in the world in the Academic Ranking of World Universities (ARWU) – its highest ranking in 13 years. ARWU, considered as one of the leading international league tables, assesses more than 1,200 universities every year using six measures and publishes data on the best 500.

For details, go to the University of Bristol News page (link).

The photo used in the news article was shot last year (i.e. 2015) when I was a PhD student at the University of Bristol – as part of a series of ‘photo shoot’s for the postgraduate prospectus.

mesut_erzurumluoglu_bristol_social_community_medicine

My photo also appeared on the University of Bristol Social and Community Medicine website (2017) with the caption: “I was impressed with the research that was going on at the Bristol Genetic Epidemiology Labs (aka BGEL) and the department’s QS ranking places the University amongst the top 50 in the world. I also liked the way I was treated by my potential supervisors (Dr. Santi Rodriguez, Dr. Tom Gaunt and Prof. Ian Day) prior to accepting the offer”.

PS: I previously interviewed the former Vice-Chancellor of the University of Bristol, Prof. Eric Thomas – for NoS Magazine. The PDF version can be found here

PPS: I’ve also modelled for the University of Leicester undergraduate prospectus (details can be found here) 🙂

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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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Difference between the lung of a COPD patient and an unaffected one. Image taken from NHLBI website (click on image to access the source)

Difference between the lung of a COPD patient and an unaffected one. Image taken from the NHLBI website (one of the leading institutes in providing information on various diseases; click on image to access the source)

Many of us will either suffer or have a relative/friend who suffers from a disease called Chronic Obstructive Pulmonary Disease (COPD, click on link for details) which is a progressive respiratory disease characterised by decreasing lung function (struggling to inhale/exhale air, irreversible airflow obstruction), very likely accompanied by chronic infections. COPD has a prevalence of over 2% in the UK population (corresponding to approx. 1 million in the UK, probably a lower bound estimate due to many undiagnosed cases; this figure is approx. 16 million in the USA) and is currently the third biggest killer in the world (only behind cancers and heart-related diseases) – costing the lives of millions (in the USA alone, number of deaths attributed to COPD is over 100 thousand); and the health services, billions of pounds.

Contrary to the well-known genetic disorders such as Cystic Fibrosis and Huntington’s disease, which are diseases caused entirely by a person’s genetic makeup and caused by mutations in a single gene, COPD is a (very!) complex disease with many genes and environmental factors (e.g. smoking, pollutants) contributing to the development/progression of the disease. This complexity makes it much harder to dissect the causes and find potential (genetic) targets for cures or therapies. However, we do know that smoking is by far the biggest risk factor with up to 90% of those who go on to develop clinically significant COPD being smokers. But only a minority (<25%) of all smokers develop COPD, indicating the strong role genetics can play in the progression of this disorder. Also not all COPD patients are smokers (up to 25% in some populations), indicating that – at least in some patients – genetics can play a rather determining role. I must stress that all the statistics I provide here can vary considerably from population to population due to different lifestyles and genetic backgrounds.

Genetic_epidemiology_genetics_mesut_erzurumluoglu

I – together with a large group of collaborators – search for genetic predictors of lung function, which helps us to identify which individuals are more likely to develop the disease and potentially understand the underlying biology/pathology of respiratory diseases such as COPD and asthma, and related traits such as smoking behaviour. To do this, we carry out what is called a genome-wide association study (GWAS, click on link for details), where we obtain the genetic data (millions of data points) from tens of thousands of COPD (or asthma) patients and ‘controls’ (people with normal lung function). To ensure that our results are not biased by different ethnicities, life styles and related individuals, we collect all the relevant information about the participants and make sure that we control for them in the statistical models that we use. GWASs have been extremely successful in the identification of successful targets for other diseases and have led to the field of Genetic Epidemiology (GE, click on link for details) to come to the fore of population-based medicine. GE requires extensive understanding of Statistics (needed to make sense of the very large datasets), Bioinformatics (application of computer software to the management of large biological data), Programming (needed to change data formats, manage very large data), Genetics (needed for interpretation of results) and Epidemiology (branch of medicine which deals with how often diseases occur in different groups of people, and why); thus requires inter-disciplinary collaborations.

GWAS results are traditionally presented with a Manhattan plot (due to its resemblance of the city's skyline) where the genetic variants corresponding to the dots above the top grey line (representing P values less than 5e-7 i.e. 0.0000005) are usually followed up with additional studies to validate their plausibility. Image taken from Wikipedia (click on image to access source)

GWAS results are traditionally presented with a Manhattan plot (due to its resemblance of the city’s skyline) where the genetic variants corresponding to the dots above the top grey line (representing P-values less than 5e-8 i.e. 0.00000005) are usually followed up with additional studies to validate their plausibility. Image taken from Wikipedia (click on image to access source)

The inferences we make from these studies can shed light in to which genes and biological pathways play key roles in causing COPD. We then follow up these newly identified genes and pathways to analyse whether there are molecules which could be used to target these and be potential drugs for treating COPD patients. Our results can be of immense help to Pharmaceutical companies (and ultimately to patients), as many clinical trials initiated without genetic line of evidence have failed, costing the public and these companies billions of pounds.

As smoking is the biggest risk factor for respiratory diseases like COPD, I am – also with the contribution of many collaborators – in the process of analysing whether some people are more likely to start smoking, stop after starting, and smoke more than usual when they start smoking. The results can have huge implications as many people struggle to stop smoking, and when they do, research suggests that up to 90% (figure differs between populations) of them start to smoke again within the first year after quitting. Smoking is not only a huge contributor to the risk of developing COPD, but also to lung (biggest killer amongst all cancers), mouth, throat, kidney, liver, pancreas, stomach and colon cancer (not an exhaustive list). In the UK alone, these cancers cause the slow and painful death of tens of thousands, alongside a huge psychological and financial burden on the families and public resources.

The “lung” and the short of it (stealing a phrase thought up by my colleagues at the University of Leicester, click on link to see who they are) is that COPD is a disease that is going to affect many of us, and any useful finding which leads to cures and/or therapies could increase the life years of COPD patients and affect the lives of thousands of people directly, and millions indirectly (e.g. families of COPD sufferers, cost to the NHS). Finding targets to help people stop smoking can potentially have even bigger implications as many continue to smoke, despite huge efforts and funding allocated to smoking prevention and cessation.

A nice TED talk about the world of Data science and Genetic Epidemiology

Addition to post (09/02/17): A Circos plot presenting results from our latest lung function GWAS (Wain et al, 2017; Nature Genetics) was shortlisted (title: Breathtaking genes) and displayed in the Images of Research exhibition (9th Feb 2017) organised by the University of Leicester

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Don’t you worry child

There was a time, when I used to look into my supervisor’s eyes

In a happy lab, I was a king, I had a golden throne

Those days are gone, now the papers are on the wall

I still hear the sound, of the articles that were torn

 

In the room with the recording tape

That’s where I had my first heartbreak

I still remember how it all changed

My supervisor said:

 

Don’t you worry, Don’t you worry child

See science can play games on you

Don’t you worry, Don’t you worry now

A Nobel’s waiting for you

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