Dr Esther Crawley: Transcript of Presentation: “The Future of Research in CFS/ME”
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In March, this year, Dr Esther Crawley gave a presentation to a Dorset patient support group entitled “The Future of Research in CFS/ME” during which she also spoke on XMRV research and delivered some very controversial comment on the operation and findings of the Whittemore Peterson Institute (WPI).
It is understood that the presentation was attended by Annette Brooke (MP for Mid Dorset and North Poole) and Vice-Chair of the re-formed APPG on ME.
Below is an unofficial transcript that has been provided to me to supplement the partial transcript ( Dr Esther Crawley discusses XMRV and Whittemore Peterson Institute (WPI), March 2010 ) which was first published on ME agenda, in August.
Care has been taken in the preparation and proofreading of this text; some transcription errors and ommissions may remain.
Dorset CFS/ME Society
Annual Medical Lecture
27th March 2010
The Future of Research in CFS/ME
It’s a great pleasure to be here, everybody, and I’m really glad actually that my talk actually fits in very nicely with what William’s just said. Phew!
I’m going to be talking a lot about the collaborative research and the first half of my talk actually was given to the MRC Working Group at the end of last year. So you’ll actually see what we were talking about where the MRC gathered lots and lots of researchers together to discuss a way forward with chronic fatigue [sic] and I did the talk on epidemiology.
And, actually, on a sort of personal level, [I am] particularly proud because my gorgeous son is sitting in the front row, grinning from ear to ear about his Mummy, so that’s a great joy and it’s lovely to see so many of you again.
Slide 1: The future of research
• Providing services and treatment
• Different disease types
• Evaluation of treatment
• Understanding the cause
• Genetics and GWAS
• Infection and XMRV?
So in the talk today, I’m going to talk about the future of research and I believe there is strongly… that there are two really important arms for research in chronic fatigue syndrome. The first is about how we [are] actually, really quickly, going to change what happens to patients and carers and, to do that, we need to understand much more about the epidemiology, and my children asked me what that meant this morning, and that’s the study of populations. We need to understand more about who it affects, how to treat it and about the different disease groups, because you all know that there are different types of chronic fatigue syndrome.
And the second arm of research is the arm into aetiology: what causes chronic fatigue syndrome. And, of course, that’s the bit that we researchers really enjoy doing. That’s the bit that makes us excited. I don’t actually agree that research is demeaning. I think that I’ve got the best job in the world, actually.
And the aetiology and the pathogenesis and my PhD was genetics. That’s what really excites us. But, realistically, it’s not going to have the same gains at a patient level or a population level as understanding more about the illness.
And, realistically, the aetiology research has to be done on a background of understanding much more about what this illness is, otherwise we’ll get the wrong answers.
So I’m going to talk about both.
And I couldn’t resist talking about XMRV. I think we have to know about what’s actually happened and I will discuss that as well and what the implications are.
So, the epidemiology. What is this illness? Who does it affect?
Slide 2: Prevalence
• NICE and CMO: “at least” 0.2 to 0.4%
• Prevalence 2.57% (USA)
• Similar: Sweden, Brazil, India etc
• Prevalence 3/12 ALPSAC [sic]* of 4.6% (0.1% housebound)
• Difference in prevalence?
• Definition (length of time & symptoms); recruitment (diagnosis or population screening)
Reyes 2003: Wichita Kansas Archives Int Med. Reeves ’07 Jordan 2000; Jones 2004; Chalder 2003; Rimes 2007
*[Ed: should be “ALSPAC”]
Those of you who read what NICE said and the Chief Medical Officer’s report on the prevalence will obviously remember that the prevalence that the Government chooses to use for this condition is between 0.2 and 0.4% of the adult population have chronic fatigue syndrome.
The reality, however, is very, very different. I do epidemiology and the prevalence in the really good studies, in the USA, but also in all other countries, is that this condition, this illness, is much more common than the Government estimates. And, in fact, the current thinking in most recent data is that this illness affects about 2.6% of the adult population.
And I’ve got slides at the end for all your difficult questions about how we classify it, and fatigue and symptoms. I’ve got lots of lovely data to back this up.
The paediatric prevalence is more common and I’m going to talk about that in a minute and you will all know that the differences in prevalence, the whole research into this area, is complicated by differences in study design, differences in definition, and differences in how we recruit. So some of the old data was [sic] taken from doctors. How good are doctors at diagnosing this condition? [Ed: Pauses for audience comments and laughter] Exactly.
And the newer studies, the ones with the higher prevalence, don’t [sic]… ignore the doctors and, actually, go and ask people at a population level about illnesses. So that’s where you get your higher prevalence.
On the bottom of most of my slides are series of references if people want to look things up afterwards.
Slide 3: Children of the 90s [logo]
• 319 (4.7%) disabling fatigue not due to other causes
• Of these:
• 178 (55.8% female)
• 80 (20% of those with fatigue) seen GP
• 119 (1.7% of total) fatigue > 6 months
• 22 fatigue > 5 years
• 7 (0.1%) housebound because of fatigue
Now, I’m just going to dip in and out of some of our research whilst talking about other research.
This is [sic] unpublished data and it [sic] needs to be cleaned up a bit but this is from the ‘Children of the 90s’ study which was a large cohort in Bristol. 14,000 children who were born in 1990 and they’ve been followed up. And we’ve looked at the prevalence of disabling fatigue in children at 13 and, by the time you’ve taken off all of the other illnesses that could cause fatigue, the prevalence of fatigue at 13 is 4.7% in children. Now, this isn’t just children feeling tired. This is 13 year olds who are not doing the things they want to do because of fatigue. So again, that’s much, much higher than previous Government estimates.
And I think this is… this actually makes my heart sink. If you look at this, out of these 319 children, 22 of them had disabling fatigue for more than five years and seven, 0.1%, were housebound because of fatigue.
So that 0.1% is actually quite close to the Government’s figures of 0.2 but these are the figures that we’re now using in terms of setting up services, so about between 2 and 4% of children have difficult fatigue and 0.1% are housebound with it.
Slide 4: School Screening
• Screened all children 3 schools missing 20% or more of fatigue
• School roll 2855
• 23 new cases of CFS/ME, 4 known CFS/ME (3 not known to service)
• 1% of children were missing 20% or more of school with CFS/ME
• Only 15% of these had a diagnosis
And this is consistent with a study that I completed a year ago. I was telling William about this at lunch. We know, and I think last time I was here I talked about the fact that doctors see people of higher socio-economic class, white Caucasians and female but, in the general population, in children, we know that this is an almost a social depravation [sic] and boys are equally affected as girls. So I was thinking, at the time I came to see you last, that, actually, that must mean that there are lots of boys in school who are struggling with fatigue and concentration and memory problems who weren’t accessing any services.
So I did a study in three schools in Bath and Bristol and I looked at all of the children who were missing 20% or more of school and, I mean, I think these are quite scary figures. So this is school roll of 2,855 children. We found 23 new cases of chronic fatigue syndrome, four had been given the diagnosis but weren’t known to our service. And, if you actually work this out, this means that in these three secondary schools, 1% of all children were missing 20% or more of school. This isn’t minor fatigue, OK, this is a day a week over more than six weeks, who turned out to have chronic fatigue syndrome and only about 15% of these had a diagnosis.
So this illness is really, really massively underdiagnosed and, if you take this further, what we found is in these children, for several of them, given a little bit of advice about sleep they were able to turn the illness round very quickly and, in fact, the majority of these children, undiagnosed ones, were better within six months, having had access to treatment and went back to full-time school.
So this really is an illness that is massively underdiagnosed and underrecognised in the UK and, of course, that makes setting up services very difficult.
Slide 5: Different Disease Types?
Is CFS/ME one illness?
Right, well, I don’t need to tell you here that this illness is not the same illness for everybody. It’s a heterogeneous illness and you’ve been telling us that for a very long time.
Slide 6: Phenotypes
• 1998 – 2008: 9 studies – 3 – 6 phenotypes
• Paediatric 3 Phenotypes: musculoskeletal; migraine; sore throat (May 09)
• Hickie ’09: 33 population studies (37,724 people)
• 5 phenotypes: musculoskeletal; neurocognitive; inflammation; sleep disturbance; mood disturbance
Nisenbaum ’98 ’04, Friedberg ’00; Sullivan ’02, & ’05, Jason ’02; Vollmer-Conna ’06; Wilson ’01; Askakon ’06; Hickie ’09 Australian and NZ J Psych; May 09 ADC
And, if you look at the literature, since 1998, there are nine studies which describe between three and six phenotypes. That’s what you present with, what symptoms you have.
Now, in children, we think there are three disease types and this paper’s published this week from our group.
And, for adults, this is the most convincing study. This is an Australian study. Look at these numbers. This is collaborative research. This… 37,000 patients across all the major Western countries and patients diagnosed at GP and at hospital level. This is collaborative research. This is what we need to be doing.
37,000 patients, five disease phenotypes. Five disease types and these are the names here.
Slide 7: Methods
• 333 young people
• Binary symptoms => factors
• Relationship between factors and:
gender, age, length of illness, depression, anxiety and markers of severity (fatigue, physical function, pain and school attendance)
Now, I’m going to show you some data from paediatric patients. It looks complicated. It’s not rocket science and I’ll talk you through it.
OK, so, in our study we looked at 333 children and we asked them about their symptoms and this is…so we asked them about headaches, tummy aches, feeling sick, sensitivity to light. All of the common symptoms.
And then we grouped these symptoms, it’s a mathematical technique, to see which ones went together and, essentially, there were three different disease groups in children.
Slide 8: Table: 3 Factors [based on original Table]
There was this one here which we call musculoskeletal and that’s because they had mainly muscle pain and joint pain.
There’s this one here that had migraine and that’s because they had headaches, nausea, light type sensitivity.
And this one here that had sore throat, mainly sore throat and tender lymph nodes.
Now, if you’re a child, you can have more than one of these and so… but the interesting thing is if the child presents at a clinic with these are they actually different in terms of severity and, therefore, ultimately, do we need to be giving them different treatment?
Slide 9: Table: Association with Severity [based on original Table]
Now, on this slide, we looked at the different types, musculoskeletal, migraine and sore throat, and looked at markers of severity: fatigue, physical function, school attendance. And you can see that this type, migraine type, is associated with worse physical function, worse school and worse pain.
The sore throat type, better fatigue, better physical function, better school attendance and better pain.
So it seems that these different presentations, these different types, are associated differently with markers of severity and that might mean that we actually need to use different treatment for them.
• There are different types of CFS/ME with different severity
• May require different treatment
• Very large well described cohort → suitable homogenous groups
• To study different aetiology
• To study different drug treatments e.g pizotifen
So there are different types of chronic fatigue [sic], different severity, they may require different treatment and what you need is you need huge groups if you’re going to study any type of treatment because what works for one disease type might not work for another.
Slide 11: Schematic: Paediatric symptoms, CFS/ME [based on original Schematic]
So this is how I think about chronic fatigue [sic] in children. So we have chronic fatigue [sic] here and you have the… this is the migraine phenotype or the migraine group, sore throat and musculoskeletal.
Now, there are some children… these are probably the housebound ones that have all three. If you look at the symptoms they have all of them and… but there are some that just really have bad headache, nausea, dizziness and so on.
Now, if you’re going to look at a drug treatment like Pizotifen, which is a drug treatment we use for migraine, and seems to be particularly effective in some children with chronic fatigue syndrome, there’s no point trying that drug on the wrong children. It’s not going to work. So you want to try it on the children here, that have got that particular disease group.
And, so, this is kind of… this type of thinking has happened in lots of other chronic illnesses and we’re at the very, very early stages of thinking about it but it’s definitely a very important way forward. And it may well explain some of the issues that we have in research in terms of small sample sizes so, if you’re trying a drug, and you tried it in all of them, so if you tried Pizotifen in all of them, it’s only going to work in a few, isn’t it? So it really explains some of the problems that we’ve had in research.
Slide 12: What is the future [of epidemiology]?
• Population studies
• Community, GP and schools
• Studies of disease groups
• Different groups? Different outcomes
• Outcome studies
• Include severely affected and children
So what’s the future for epidemiology? Well, the MRC believe, and I agree, that we need lots of large population studies. We need more studies tackling chronic fatigue [sic] at the population level. For me, that means looking at chronic fatigue [sic] in schools, at GPs’ surgeries and in the community. I believe very passionately that for children, in particular, we should be looking at prevention strategies. We need to understand more about the different disease groups and the different outcomes. We need to understand more about the different treatments.
And we must include the severely affected and children.
Slide 13: British Association CFS/ME
• DH funded clinical services 2004
• 13 centres, 38 adult clinical teams, 11 paediatric teams
• ~6000 adults 600 children p/a
• 2009 merged with CFS/ME network
• Estimated 7000 – 8000 new patients a year
One way round a lot of this problem with sample size is exactly what Stephen Holgate was talking about so, when Stephen was setting things up, we too were setting things up and, last year, we formed the British Association for Chronic Fatigue [sic]/ME. I’ve been very fortunate, or unfortunate depending on your view on workload, to chair this…I’m coming up to…I’m nearly finishing my third year now.
And this is an amalgamation of all the Department of Health funded clinical services, plus all the research groupings, for chronic fatigue syndrome in the UK. And there are 13 centres, 38 adult clinical teams and well over 7,000 adults and children that are seen every year.
Slide 14: Maps of England: Adult and paediatric services
And you’ve seen this map before. These are the adult services and the paediatric services in the UK.
Slide 15: Minimum Data Set
• Aim: Benchmarking & Infra structure
• At assessment:
• Demographic data, age, postcode, sex, ethnicity, area of residence, employment status and hours worked/in education, time to assessment
• Inventories: 11 item Chalder fatigue, SF 36 (physical function), HADS, pain VAS, 12 month goal
• MDSv2: Symptom check list (different disease groups)
• Follow up – 12 months
And, as part of this, one of the things that we’ve said is that, if you’re going to join this group, you need to sign up to benchmarking. That means we need to compare services with each other and understand if a service is particularly successful…[if] Dorset service outstrips our service, then I want to learn from them. So we need to understand who is successful and what we can learn from it.
But also, all the patients that are seen in the service get all of this [sic] data collected. You’ll see here a whole load of data on employment status and hours worked, ‘Chalder Fatigue’, ‘SF 36’, and, in the new version, we’re going to have a symptom check list follow up at 12 months.
Now, the main purpose for this is to be able to look at the different services and benchmark the services but one of the added advantages is what Stephen Holgate is talking about is this already provides a fantastic infrastructure for future research and this is why we’re now able to do the really, really huge genetic studies that I’m going to talk about at the end of this talk.
Slide 16: National Outcomes Database
• 2006: Regional Database
• 2009: Regional to National Dataset
• 30 teams contributing data
• Assessment data >3500 adults and children
• Estimated 5000 adults and children a year
• Probable 75% follow up
Right, so this is a database that we set up about three or four years ago. This is in my office, I’m proud to say, and we currently have well over 4,000 adults and we’ve started to benchmark services.
OK, so, I’m going to just talk you through a little bit of some of the data.
Slide 17: Adult data
• Centre A and B 1918 Adults
• Gender: Female 74.6%
• Ethnicity: 96.8% white
• Unemployed: 534 (27%) CFS/ME
• Time to Assessment: 427 (25%) >5 years; 329 (19.4%) >10 years
So these are two anonymised centres, we anonymise them all for obvious reasons, and you can see the expected ratio, 75% of them are female, mostly white.
Look at this figure here. This is very powerful for commissioners. 27% of the people that came to the service were unemployed because of chronic fatigue syndrome. Time to assessment. Five years to get an assessment and one fifth more than ten years. I mean isn’t that still… that’s shocking. That’s data from last year. These are two well established services, huge services with, you know, a lot of awareness training and so on. I mean I think this data is going to be very, very useful for commissioning more services.
Slide 18: Illegible graph
And, I don’t know if you can see from the back, but this is our first comparison benchmarking of services. So this is the ‘Chalder Fatigue Scale’ and the first lines…these are all in pairs. Here, one pair, two pairs, that one hasn’t got any follow up, pair, three pairs. And you can see that almost all the services….that’s at ‘Chalder Fatigue’ at assessment and that’s at follow up. Assessment, follow up. Assessment, follow up. Assessment, follow up.
And this is physical function. Physical function should get higher if you get better. So, assessment, follow up, assessment, follow up, same here, but very wide confidence intervals. Assessment, follow up.
So, on the whole, services are actually getting people better.
Small sample size, early days, but you can see that when we get a larger follow up numbers we’ll really be able to start to explore the differences between services.
Slide 19: Measuring impact
Financial and societal
Now, this is my pet topic. William said research happens by chance and I think that’s right actually and it happens because you do research with people that you love doing research with and it happens because fantastic people come and say “Can I do some work with you?”.
And this was kicked off by my psychologist who wanted to do a research project and I was particularly keen to start studying the impact chronic fatigue syndrome has on families because no-one has done that piece of work.
Slide 20: Measuring impact
• Develop tools
• Financial, societal, quality of life
• Patient and carer
• Impact on families study
• Most parents ↓ income (mean £247.month)
• Most ↑ expenditure (mean £206/month)
Now, for measuring impact, there are lots of issues we’ve got to consider. First of all you have to measure the tools. You’ve got to work out how to do it and, in chronic fatigue [sic], no-one’s done it before so we had to do that. You have to make a decision. Are you going to look at the NHS..? I’ve been on a health and economics course the last three days so I’m really into this now. You have to decide are you going to measure the NHS financial cost, society costs, quality of life. I believe very passionately that we should look at the impact on patients and carers rather than the NHS and, in this study that she did, she looked at families.
It was a mixed methods paper which means that we collected a lot of data on a lot of families and then talked to families. Strange concept in research is actually talk to the people who are involved in the illness. And what we found… look at this figure. This has just gone to publication. Most parents of children with chronic fatigue [sic] had a reduction [in] income of £247 a month because of loss of earnings. I mean that’s a big deal, isn’t it?
And, at the same time, most of them had an increase in expenditure of £200 a month. OK, and you won’t be surprised to know … I mean our sample size was small but it looks as if the families with the biggest drop in income were also the ones with the biggest increase in expenditure.
And we need more studies like this to be able to go to Government and say, you know, these families are really suffering and also to say, when we get them better, and the parents go back to work, their income goes up again.
OK, so, that is the epidemiology, what happens to families, the different disease phenotypes and how we can use that research data to change what happens to chronic fatigue [sic] services in the UK.
Slide 21: Aetiology and causes
And now I’m going to talk about the perhaps more interesting, definitely more cool, bit of research, the one that we all enjoy, but, probably is going to have less of an impact for you as patients, but it’s definitely more interesting to talk about.
Aetiology and causes. Well, actually, that’s [a] really rubbish sentence. Aetiology is causes.
Slide 22: What causes CFS/ME?
• Evidence for
• Genetic vulnerability
• Environmental insult
• Maintaining factors (eg hypothalamic-pit factors)
Let’s talk about the causes of chronic fatigue syndrome. So what do we know about the causes of chronic fatigue syndrome? We know that chronic fatigue syndrome is genetically very heritable. We know that this illness runs in families. There are loads of twin studies to show it runs in families and you are basically genetically vulnerable. It’s not a given that your children are going to have it. It’s rather like asthma or bad backs or my family all being giants but it makes it much more likely.
And then you can have your genes all your life. You then need your environmental insult and the environmental insult for most people is which virus….? Which is the most common virus for chronic fatigue syndrome? [Ed: Waits for audience response] Glandular fever virus, yes. The Epstein Barr virus, streptococcus, and so on, are all very common and then you have your maintaining factors. That’s the ones that keep you sick and that can be a variety of different things.
So that’s our model.
Slide 23: Genome Wide Association Studies
• Candidate genes: use “conventional” knowledge: the biological basis of disease
• GWAS: generate novel hypothesis – doesn’t rely on current knowledge
Now, I explained this to XXXX this morning and he got it so I’m going to have another go with you lot.
There are two ways of looking at genes. Now, we’re not talking about gene expression. That’s another area which I’m happy to talk about. We’re talking about the genes that cause the illness.
The first way is that you can come up with an idea. So, you can say, “Well, I used to do arthritis and I saw fatigue and I know what causes arthritis so I want to look at those genes”. That is limited by your imagination. It’s limited by your ideas and, in medical-speak, that’s limited by your hypothesis that you can generate.
The second way, and I don’t know how many of you have seen… How many of you have seen the newspaper headlines talking about genes and obesity? How many saw those? Yeh? [Ed: Waits for audience response] [Indecipherable] Good boy, XXXX.
Genes and obesity and asthma and so on, ok. This is the new big thing in genetics and it’s huge. So this is called genome-wide association studies and you don’t need any prior knowledge. You don’t need any hypothesis. You’re not limited by your imagination, because what genome-wide association studies do is they take all of the genes in huge numbers of patients and compare them to absolutely massive numbers of controls. And this has actually transformed our knowledge about a whole heap of common illnesses and the title down here is the genetic susceptibility to type 2 diabetes.
And one of the very important things I’m going to talk about in a minute is that you can use genome-wide association studies to tell you more about the different types of illness.
Slide 24: What lies behind these confirmed associations?
[Images of chips]
Now we have the ability to ask all available genetic hypotheses at the genetic level simultaneously and to avoid bases of candidacy.
Cost: less than £100 per 500,000 variants one individual
OK, this is what we use in genome-wide association studies. This is one of the chips. Anybody want to tell me how much this costs? XXXX, you’re not allowed to say. [Ed: Waits for audience response] Sorry? Thousands. Any advance on thousands, up or down? Millions? Hundreds of thousands? Well, you’re all luckily wrong. OK, these cost less than £100 per 500,000 genes in an individual.
So what’s happened over the last few years is the technology has massively expanded. They had a little issue with the maths (which I could talk about if you’re interested) but, once they cracked the maths, this became such a big deal that the price has plummeted.
So £100 per person would do 500,000 SNPs. And, basically, what you do is you have fragments of DNA on these and you run DNA over them and they stick in various places and that tells you what your DNA type is.
Slide 25: Used for new genes
• Heart disease
And, in the last couple of years, this method has been used to find the genes associated with obesity, asthma, height, blindness and heart disease. So what do you think I want to do? Fatigue. Fatigue.
Slide 26: Letters [to] Nature Genetics
Meta-analysis of genome-wide association and large-scale replication identifies additional susceptibility loci for type 2 diabetes
Slide 27: Phenotype heterogeneity
BMC Medical Genetics [Ed: heading from text of paper, illegible]
OK. Now, the important thing, as I said earlier, is that you can use these techniques to look at the different types of illness. So you saw these two slides and what they talk about is type 2 diabetes. Several people in this room will probably have type 2 diabetes and we’ve known for a while that you can get type 2 diabetes in thin people and in not thin people. And what happens when they did chronic fatigue syndrome… so a genome-wide association study… so this is the output you get for genome-wide association studies, so these are all the genes of everybody at sort of normal frequency. And do you see here? This is the FTO gene and here are the other ones.
Now, the FTO gene is associated with the diabetes of not thin people and, actually, that’s the gene that was found to be causal in obesity but, in the thin people with type 2 diabetes, here are the genes. Do you see these spikes? So different genes produce different types of illness even though the illness looks similar in both groups.
Slide 28: Graph [based on original Graph]
And this is very early data from our kids with chronic fatigue syndrome in the ALSPAC cohort and this shows interesting genes up here in kids with chronic fatigue syndrome so we’ve obviously got to do it in much larger numbers but there’s definitely going to be something that’s going on. Well, I think so.
Slide 29: Assuming accurately measured collections of large size
• What is the underlying genetic architecture?
• Could multiple, common genetic association underpin shared aetiological characteristics?
• Might new therapeutic targets be revealed through heritable characteristics?
• Could modifiable risk factors for CFS, regardless of biological route to outcome, be confirmed?
Now, the thing… so the reason why we do it is this bit here. What we’re interested in doing is finding risk factors that we can change. So that’s either going to be drug treatments or other risk factors that we can change. So, for example, if we found a gene that meant you were exquisitely sensitive to the Epstein Barr virus we might actually look at treatments to help you react better to it or something like that. So it’s all about therapeutic targets and risk factors.
Slide 30: Large size
• 2000 to 5000 for first study
• 2000 to 5000 for replication study
• UK – only place in the world where this can be done
The problem with the genome-wide association study is that you need at least 4,000 patients for your first study and 4,000 controls to show that you’ve got it right and you need 16,000 … sorry, 4,000 patients the first, 4,000 for the second and 16,000 controls for each.
Where in the world do you think we can do a genome-wide association study? [Ed: Waits for audience response] Here. Here. England is the only place in the whole world where we can do this type of study. Why? Because we set up a large collaborative of clinical centres and patients in clinical centres and patients want us to do this study. So, next time you go and see one of your clinicians, if we’re lucky with our funding, and we hope we will be, you may be asked to spit in a pot and, if you are asked to spit in a pot, please do, because this is how we’re going to tackle this problem.
The UK is the only place where the clinicians and researchers are working together and we are. We’ve put a grant into the MRC. It has all of the people working in research and genetic research, [they] have all got their names on the application to the MRC. “Please give us £2½ million so we can do this study.”
Slide 31: Infection
Slide 32: Risk Factors
• Known: Older age; female; lower SE class; heritable component; infection
• Trauma: Heim ’09 Retrospective case – control
• Ethnicity: Dinos ’09: meta analysis – ↑Native Americans OR 1.5 (CI1.08 – 56.4)
• Mood: Harvey ’08 “Psychiatric illness” in adults
• Systematic review: Hempel 2007: none replicated
Hempel 07; Katz 09; Heim 06 & 09; Kerr 08
These are the known risk factors for chronic fatigue syndrome. We’ve already talked about heritability, lower socio-economic class, older age, female and infection. For a long time, we’ve known that infection was a trigger for chronic fatigue syndrome. All these other ones have not been reproduced.
OK, so people talk about it, not been reproduced, don’t know if they’re true or not.
Slide 33: Which infections?
• EBV (Dalrymple ’64, Thompson ’69, Lambore ’91, White ’98)
• Viral Hepatitis (Berelowitz ’95)
• Viral meningitis (Hotopf ’96)
• Q Fever (Ayres ’98)
• Viral infections (Cope ’94) OR 1.45 (CI 1.14-2.04)
• Parvovirus (Kerr 08)
• Enterovirus (Kerr 09)
And you’ve already told me that the most common infection is the Epstein Barr virus. This is the one that is associated with glandular fever but all of these infections are associated with chronic fatigue syndrome.
In kids, we see lots of children after viral infections.
Slide 34: Infectious mononucleosis
• 301 adolescents identified monospot + IM
• 6 months: 24% not fully recovered, CFS/ME 13%; 1 yr CFS/ME 7%; 2 yrs CFS/ME 4%;
• 250 Adults primary care (123 monospot+ IM & 127 URTI)
• Monospot+ OR 1 month 1.8, (1.13-2.87); 2 months 2.47 (1.47-4.14); 6 months 2.14 (1.37-3.34)
Katz ’09, White ’01
And, if you look at the rate that you produce chronic fatigue [sic] after infection, it’s much higher than you would think. If you are a teenager and you get the Epstein Barr virus (this is from an infectious talk, by the way, so it’s slightly complicated, trying to pick out the highlights), if you get EBV, at six months, 24% are not fully recovered. That is a lot, isn’t it? And, at one year, 7% are not fully recovered. And, at two years, 4% [are not fully recovered]. Got chronic fatigue syndrome.
In adults it’s not too different. One month… well these are the odds ratio but, essentially, at one year it’s still about 5 or… to 8%.
Slide 35: Infection factors
Hickie ’06: 253 adults EBV, Q fever or Ross River virus
• 12% developed disabling fatigue
• 11% met CDC criteria
• Predicted by severity of initial infection
Hickie BMJ 2006 575
And this is a beautiful paper. I love this … oh, I haven’t ever met him actually and, in fact… no, he’s Ian Hickie so it is a bloke, but he does beautiful research so this is a lovely paper where he looked at the development of chronic fatigue syndrome after Epstein Barr virus, Q Fever and Ross River virus (we don’t see these two in England) and what he showed was that whether or not you got chronic fatigue syndrome was actually predicted by how bad your first illness was. So, if you get a really, really terrible viral infection, a really bad bout of glandular fever, you are much, much more likely to develop chronic fatigue syndrome.
Slide 36: XMRV
Image: Front page of Independent
Image: Artist’s impression of Center for Molecular Medicine, Reno, Nevada
Image: Illustration of XMRV virus
XMRV. OK, so in the next, last, remaining bit of the talk I want to summarise what’s happened about the XMRV story for you. I think it’s really important that we’re all informed about it. Many of you will have woken up and read this story, in fact I knew about it 24 hours before it was about to break – “Has science found the cause of chronic fatigue syndrome?” – we’re all very excited and hopeful this might give us something we can treat. Great.
Don’t you think this is the most beautiful picture? That’s the XMRV virus. I don’t know how they get those colours on them – very beautiful. Now this is the Centre that reported it.
Do any of you notice anything about that picture? XXXX you’re not allowed to say. Sorry?
Member of the audience: Sunshiny?
EC: Sunshiny, yeah. It’s in Reno, yeah, yeah. Anything else? It’s a bit far away. Has anyone looked at the website?
Isn’t that interesting? That doesn’t exist. That’s a fake picture – it’s what they would like to exist, when you donate money, when you go on the website.
I thought everybody knew that! Yeah, sorry? This is Dorset. OK. The Centre isn’t built. That’s their picture of what they would like to build and when you go on the website it has “Please donate.” OK. What do the Lombardi group originally show?
Slide 37: Detection of XMRV in patients with CFS
• Nested PCR for gag sequences 68/101 CFS and 8/218 controls
• Expression XMRV proteins
• Intracellular flow cytometry
• Western blot
• Is it infectious?
• Co-culture with permissive prostate cancer line
• Stimulates immune response?
• Flow cytometry to detect antibodies
Lombardi Science 2009
OK. This is a complicated slide. I’m just going to take you through bit by bit because it’s really important when we look at all the research evidence. OK. The gag sequences – the DNA that’s associated with these particular type of viruses – so they use PCR. PCR is basically when you get a tiny bit of DNA and you multiply and multiply and multiply and then you run it on a gel and see if it’s there. And what they found, and you’ll all remember these figures, I’m sure, is that they found it in 68 out of 100 [sic] [Ed: 101 on slide] chronic fatigue [sic] patients and 8 out of 218 controls.
They then looked in the cells and they found the protein in the cells and then they looked at whether it’s infectious. Now I have to say, this bit made me slightly worried – so they looked to see whether this virus could infect other cells within the lab and they showed that it’s infectious and they also looked at what happened if you put the virus with other cells in terms of did it develop an immune response?
Image: PCR A: CFS; B: controls
Image: A: Expression of XMRV proteins IFC; B: Western blots CFS; C: Western blots controls; D: flow cytometry
Image: A: western blot of lysates of prostate cancer cells; B: EM of cells infected; C: EM of virus particles releases by infected cells
And these are some of the pictures they showed. So when you multiply out the DNA, you then run it on a gel and you tag it with a thing that shines – I did my PhD doing this, I can tell you all sorts of awful stories of gels breaking and all sorts of other things going wrong. But these are the chronic fatigue [sic] patients – you see all these lines, here? That’s that gag sequence – here and here – that’s the end of the line and these are the controls.
Then they looked at the expression in cells and you could see it. And then they looked at the infection and this is the infection happening here. Now this paper went out for review by virologists – not by clinicians and that’s a very important point and it was passed and it was published.
Slide 39: From their website
We have detected the retroviral infection XMRV is greater than 95% of the more than 200 ME/CFS, Fibromyalgia, Atypical MS patients tested. The current working hypothesis is that XMRV infection of B, T, NK and other cells of the innate immune response causes the chronic inflammation and immune deficiency resulting in an inability to mount an effective immune response to opportunistic infections. (see [illegible] in Science.)
And this is what they said on their website and I think this is kind of interesting:
“We have detected the retroviral infection XMRV is greater than 95%…”
Where did the 95% come from? Did anybody notice the 95%? Can anybody remember the percentage they found it in? Yeah, 66% [sic], slightly less. OK. Says on the website “…95%…The current [working] hypothesis is that [XMRV]…” infects these cells…and I found this absolutely terrifying…viral chronic fatigue syndrome “causes the chronic inflammation and immune deficiency resulting in an inability to mount an effective immune response to opportunistic infections.”
OK. Have they shown any of that? Have they shown increased risk of opportunist infections? Have they shown a defect in the immune system that’s actually going to affect someone rather than just in a cell lab plate?
No. But that’s what’s on their website. That’s what they say they’ve found.
[Image of people jogging]
So what happens? The research community runs to replicate the work.
“Failure to Detect the Novel Retrovirus XMRV in Chronic Fatigue Syndrome”
[Copy of top PLoS ONE article – title and authors only]
OK. And you’ll all remember when this first paper came out “Failure to replicate…” – this is an English paper [Ed: the McClure PLoS ONE paper]. Well obviously this is wrong because they didn’t use the same techniques and it wasn’t the same patient group.
• 186 well characterised patients, CDC diagnosis, all examined, median length of illness 4 years
PCR XMRV specific and conserved murine retroviral sequence
• Positive and negative controls, blinded PCR and virus free lab
• 0/186 positive for XMRV
So in this particular experiment, they actually characterised the patients. Now on the original paper, they say that the chronic fatigue [sic] patients were well-characterised but they do not describe them at all. We don’t know how many were girls – we don’t know how many…girls! – I’m such a paediatrician – we don’t know how many were female. We don’t know how long they had had the illness for. We don’t know who diagnosed them and we don’t know whether they had any blood tests to exclude other illnesses.
In this one, [Ed: the McClure paper], they actually had all the exclusion stuff excluded, they then used the DNA sequence. They had positive and negative controls. Why do you need positive and negative controls? Yes, so you’re worried that maybe when you do PCR it’ll pick up…you’ve all seen crime scenes, right? So PCR will pick up one bit of DNA, so if you’ve got a bit of DNA in your solution or something like that, you must have negative controls because you need to be certain that the DNA has come from the samples – not from your lab solutions.
Yes. OK. And you must have positive controls to make sure your experiments work. They used a virus free laboratory. So they did it in a laboratory that had not had the virus in the past and they blinded the person doing the PCR. Does everyone know about “blinding”? So what they did, was that the person that was reading the gels didn’t know whether they were patients or not, because it’s really easy on those gels to over-interpret what you see. OK and their results, you might all remember, they didn’t find any out of 186 patients – none of them had chronic fatigue [Ed: corrects herself] – XMRV.
Slide 43: And then another one
“Absence of xenotropic murine leukaemia virus-related virus in UK patients with chronic fatigue syndrome”
[Copy of top Retrovirology article – title, reference and authors only]
And then a few days later, this one came out. This one had several people from England – Jonathan Kerr and so on. And they’re very open – they said, John Gow – these are all people that we’re collaborating with – they said we wanted to find chronic fatigue syndrome – we wanted to find the XMRV virus. We wanted to – we looked hard.
• 170 patients and 395 controls
• Quantitative PCR and serological responses
• 0/299 samples detected XMRV
• 26/565 detected XMRV neutralising activity but only one from CFS/ME patient
• Most sera neutralised other viruses cross reaction
Now the criticism of the previous paper was that they hadn’t used the same techniques, so in this one they used the same techniques. They had 170 patients, 395 controls. You can already see the sample size is much bigger and they did both PCR and looked at the serology. They found none in 299 samples of patients – had chronic fatigue [Ed: corrects herself] – had XMRV. And although they found what’s called “neutralising activity” they looked at this further and suggested that the immune response was actually related to other viruses and not to the XMRV.
Slide 45: And then
“Prevalence of xenotropic murine leukaemia virus-related virus in patients with chronic fatigue syndrome in the Netherlands: retrospective analysis of samples from an established cohort”
[Copy of top BMJ article – title, reference and authors only]
And then this was published a couple of weeks later [Ed: BMJ paper] – from the Dutch group.
• Well described Dutch cohort: 76 patients, 69 neighbourhood controls
• Real time and nested PCR, +ve & -ve controls (methodology from prostate cancer research)
• For the nested PCR – 100% conserved GAG -I.R2
• Used same primer sets as Lombardi
• Despite several attempts to increase sensitivity, all samples negative for XMRV
Again, a very well described Dutch cohort – smaller, 76 patients 69 controls. And what they did, they actually went completely overboard with trying to find it. They used very, very sensitive techniques that should have detected – if any was there at all, they should have detected it – much more sensitive than the original paper and they looked at a variety of DNA and they tried several times to improve the sensitivity – all samples were negative for XMRV. So what do you think’s going on?
Member of the audience: Publicity.
EC: Publicity…I have actually given a clue.
Member of the audience: Money?
EC: Sorry? Money…money…money…
Member of the audience: XXXX wants to tell us.
EC: OK, go on, XXXX…
EC’s young son (in front row): Did they all do it from one place?
Slide 47: Why did they fail to replicate?
• Are they the CFS/ME patients?
• Paper: “well characterised” no details
• Lisbon: 2009: Samples from outbreak of CFS – Lake Tahoe 1984 – thought to tbe viral
• Binding of PCR operator, virus free lab, accredited lab, controls
• USA Vs UK?
• Prostate: Association from USA: (schalburg 09; Urisman 06);
• No association in Europe: (Hohn 09, D’arcy 08, Fischer 08)
• Conflict of interest?
• $650 diagnostic test for patients
EC: Yes! The first group – actually, the question is, was the first group chronic fatigue syndrome? And eventually, when they were asked, they told the research community that, this is in Lisbon, at the end of last year, that all the samples came from an outbreak of chronic fatigue syndrome in one village in Lake Tahoe. And when you actually go and have a look at all the research data around that outbreak, everybody at that time thought it was a viral infection. And nobody could find the virus. So most of us think that that was probably the issue – it was probably a viral outbreak that has certainly caused chronic fatigue syndrome but is not necessarily going to be relevant for us here in the UK.
It’s not clear about the PCR operator, the person that looks – it’s not clear from the paper, whether they were blinded. There might be issues about whether you work in a virus free lab, remember they showed that this was infectious. And there’s a big question here [Ed: indicates on slide] – this XMRV virus was initially described with prostate cancer and the prostate research community has shown this in prostate cancer in two studies in the USA. These are different labs in different studies but no association in Europe.
So maybe this is a virus that’s important in America but not important in this country – it’s not clear. And I think this is of interest. Within a week of their paper being published they produced a test for the XMRV virus at $650 a test.
And if I was developing a test, I would declare that as a conflict of interest on the paper – “I’m developing a test for this.” Then people can make up their mind about whether it has affected the results. We don’t know, it wasn’t declared they’d produced a test.
Slide 48: Why are patients so upset?
Why are patients so upset? OK, well I don’t know and you’ll probably be able to tell me more than I can tell. But I think when they first publicised this they went on everything, lots and lots of American television.
[Slide 48 bullets revealed]
Why are patients upset?
• New York Times: October 12th 2009
• “The new report has intrigued scientists, been seen as vindication by some patients and inspired hope for a treatment.”
[Reads from slide]
“Vindication” they said, “This “[new] report has intrigued scientists, been seen as vindication by some parents [Ed: corrects herself] – patients and inspired hope for treatment.”
Well you know, the history of this condition is that patients have not been listened to, they’ve been dismissed, they’ve had a terrible time and if a virus comes along as a cause, that is going to be seen as a vindication – I can understand that.
And it’s very disappointing, isn’t it, the negative replications?
• “Here you’ve got your immune system working well and the virus and the immune system are coexisting just fine and then some other bug, where it be Lyme, a flu, anything, gets you… and then you’ve just tipped the scale to where your immune system can’t handle [XMRV] or anything and everyday you’re seeing new infections.”
But I do think that there’s been other stuff that’s been going on that I have particular difficulties with. When I prepared this talk for an infectious diseases conference, I went through and I just got some quotes off the web from the research team. Look at this: [Reads from slide]
“Here you’ve got your immune system working well and the virus and the immune system are coexisting just fine and then some other bug, whether it be Lyme, a flu, anything gets you… and then you’ve just tipped the scale to where your immune system can’t handle [XMRV] or anything, and every day you’re seeing new infections.”
• “While it’s not advisable to take highly toxic anti-retrovirals without tests confirming effectiveness, she says some available therapies may help, including: immune modulators; anti-inflammatories, because inflammation activates XMRV; things that improve natural killer cell function; medications that help level progesterone levels, because progesterone up-regulates XMRV in lab tests; avoiding stress.”
• “Dr Mikovits says it appears that early infection (say, in children) can lead to more severe disease later on. She stresses that, as with HIV, early detection and intervention are important to keep viral loads from getting high.”
And then at one point, rumour has it (and I couldn’t find any evidence for this) that they started to suggest that patients with chronic fatigue syndrome should have anti-retrovirals, ie HIV drugs. They’ve taken that back, and this is all I could find:
[Reads from the slide a quote in which Dr Judy Mikovits is being quoted]
“While it’s not advisable to take highly toxic anti-retrovirals [without tests confirming effectiveness], she says some available therapies may help, including: immune modulators; anti-inflammatories, because inflammation activates XMRV, things that improve natural killer cell function; medications that help [level progesterone levels, because progesterone up-regulates XMRV in lab tests]; avoiding stress.”
It appears – and this really upset me, OK. All of their studies are in adults. OK, all in adults. And then they say:
“Early infection in children can lead to more severe disease later on.”
Early detection? Oh, that’ll be that test that they produced for $605 [sic] a pop?
[Reads from the slide]
“…and intervention important to keep viral loads from getting high.”
I find that really frightening. If I had a child with chronic fatigue syndrome and I read that on the web, the first thing I’d do, I’d go and buy the test, and the second thing I’d be doing would be phoning an infectious disease doctor which is what’s happened and ask about anti-retrovirals for my child, having read that.
So I do feel as researchers, we do take some responsibility for saying: This is a first paper! Let’s wait and see what happens.
You know, I think it’s really interesting, it look likes they did find something in a group of patients and we haven’t found it here. That’s really interesting and is deserving of more research. But let’s just say, it’s interesting at the moment, rather than all of this speculation, which I think can be very harmful for patients.
Slide 51: The future for infection?
• Replicate studies in both labs and understand the differences
• May be important for a subtype of CFS/ME
• Inter-relationship between infection, genetics and CFS/ME
The future for infection. OK, I gather that this may well already have happened, not been published, the way forward in these things is to replicate the studies in both labs and try and look at why there are differences. I think it may be important for a subtype of chronic fatigue syndrome. I very much doubt it effects all of them, as they claim. It doesn’t appear to be important in this country. And there’s actually very beautiful research which we need to understand more, looking at the relationship between genetics, infection and other things like mood.
OK. After a whistle-stop tour of most research on chronic fatigue syndrome, this is now my summary slide – this is what I’ve talked about.
Slide 52: In summary
• Providing services and treatment
• Different disease types
• Evaluation of treatment
• Understanding the cause
• Genetics and GWAS
• Infection and XMRV?
There are two arms for research in chronic fatigue syndrome and I don’t believe that one replaces the other. The funding for both arms is different in this country and they both need to be done together and both influence the other.
The first is important for providing services and treatment:
We need to know more about how common this is.
We need to understand who it affects.
And we need to know about the different types of chronic fatigue syndrome.
We need to understand how the different types influence treatment.
We need to know much, much more about the impact of this devastating condition on patients and carers.
The second one is that we need to know more about the aetiology, about the causes of this condition and in my view, the fastest way forward is to use the large, very large sample sizes that we have available in this country to conduct rigorous genome-wide association studies and I’m not so certain about the role of infection but I do think there is an interesting story with XMRV that we need to get to the bottom of.
Slide 53: Thanks to
• Alan Emond & CCAH Bristol
• Andrew Haig Ferguson, Lou Morphey, Rodney Sau[illegible]
• Peter Shiarly
• Collaborators: Jonathan Sterne, Margaret May, Linda Hunt, Andy Ness, George Davey-Smith, Paul Stallard
• The Clinical team: Heather Hill, Avril Missen, Jackie CC, Bev Knops, Carol Salter
• The children and their families
Logos at foot: NHS National Institute for Health Research; The Linbury Trust; Action for ME; University of Bristol [on all charts]
Logos to right: Centre for Child and Adolescent Health; AYME
And it just remains for me to thank my funders – I’m funded by the National Institute of Health Research and my Clinician Scientists Fellowship, the Linbury Trust, Action for M.E. and I’m the Medical Adviser for AYME.
And this is where I work [Ed: Points to ‘Centre for Child and Adolescent Health’ logo].
Thank you very much.
The presentation was followed by a Q and A session which included questions about the RNHRD NHS FT/University of Bristol Lightning Process pilot study in children which was granted ethics approval in September, this year, and for which Dr Crawley is lead researcher.
In his letter to Church Times, 8 October, 2010, Canon, Prof Robin Gill refers to an ASA ruling handed down to a Bournemouth company, in June, this year. This ASA adjudicaton concerns the company of Lightning Process practitioner, Alastair Gibson (“Withinspiration”). Mr Gibson is a member of the Lightning Process pilot study research team. Fiona Finch (Director, Phil Parker Group) and Phil Parker are also collaborators in the pilot study and all three are listed in the application for research ethics approval and Study Protocol document. It understood that Mr Gibson also attended Dr Crawley’s presentation.
1] SMILE – Specialist Medical Intervention and Lightning Evaluation documents (Lightning Process pilot study – children [now aged 12 to 18] with CFS and ME)