Thursday, February 25, 2010

Celiac disease – Genetic testing and clinical utility

Celiac disease is a digestive disease that damages the small intestine and interferes with absorption of nutrients from food. People who have celiac disease cannot tolerate gluten, a protein in wheat, rye, and barley. Gluten is found mainly in foods but may also be found in everyday products such as medicines, vitamins, and lip balms. When people with celiac disease eat foods or use products containing gluten, their immune system responds by damaging or destroying villi—the tiny, fingerlike protrusions lining the small intestine. Villi normally allow nutrients from food to be absorbed through the walls of the small intestine into the bloodstream. Without healthy villi, a person becomes malnourished, no matter how much food one eats. Celiac disease is both a disease of malabsorption—meaning nutrients are not absorbed properly—and an abnormal immune reaction to gluten. Celiac disease is also known as celiac sprue, nontropical sprue, and gluten-sensitive enteropathy. Celiac disease is genetic, meaning it runs in families. Sometimes the disease is triggered—or becomes active for the first time—after surgery, pregnancy, childbirth, viral infection, or severe emotional stress (NIDDK).

CD is caused by a reaction to gliadin, a prolamin (gluten protein) found in wheat, and similar proteins found in the crops of the tribe Triticeae (which includes other cultivars such as barley and rye). Upon exposure to gliadin, and certain other prolamins, the enzyme tissue transglutaminase modifies the protein, and the immune system cross-reacts with the small-bowel tissue, causing an inflammatory reaction. That leads to a truncating of the villi lining the small intestine (called villous atrophy). This interferes with the absorption of nutrients, because the intestinal villi are responsible for absorption. The only known effective treatment is a lifelong gluten-free diet.

From a genetic testing point of view CD is an interesting case, the majority (>97%) of people with CD have either HLA DQ2, DQ8 or both and the number of alleles also influences the risk of developing the disease. Having said that, roughly 30% of the population carry one or more of these alleles but the prevalence of CD is only around 1-2%, so the HLA alleles are necessary, but not sufficient, for the development of celiac disease. They are not particularly predictive either (although homozygous DQ2 and DQ2/DQ8 have a much higher risk, of the order of 1/7-1/10 – Megiorni et al, 2009) so is there any use in testing for these alleles in asymptomatic individuals?  The interesting thing is that a genetic test based on HLA alleles has an almost perfect negative predictive value, if the HLA alleles are not there then the chances of developing, or of any symptoms being due to, CD are minimal, move on to the next candidate for the diagnosis. There are also arguments in favour of testing based on some interesting facts about CD:

1. The majority of people with CD don’t even know that they have it, only about 10-20% of cases have been diagnosed, the rest remain undiagnosed for a variety of reasons, mainly because symptoms are not yet so severe that they lead to diagnostic testing. The diagnosis itself is not so easy either, the full diagnosis requires a biopsy of the intestine and histological examination of the villi to establish that they are damaged (JAMA commentary).

2. The biopsy is the final diagnosis if the individual tests positive for anti-TG (transglutaminase) and/or anti-endomysium antibodies. In most countries (at least in Europe) the biopsy is required to be positive before there is any reimbursement of gluten free foods, which are quite expensive. This is not really a good situation, often it is the case that gluten sensitivity is suspected and the sources are eliminated leading to some recovery – at this point, if the patient wants reimbursement he/she has to become ill again, and not trivially since it involves actual physical damage to the small intestine.

3. CD is on the increase, in the USA levels are 4 fold higher than 50 years ago, and this is not because of better diagnosis as the samples were compared to actual stored blood samples, the data reflect a true increase in the prevalence of the disease (Rubio-Tapia, et. Al, 2009)

4. Approx 50% of people with type 1 diabetes showed some immunological reaction to gluten and other wheat proteins and about 10% are actually diagnosed as CD (Mojibian, 2009)

5. CD sufferers have higher mortality, as described in a recent study of >40,000 individuals (Ludvigsson, 2009), but the surprising finding was that even higher mortality was seen in the antibody positive but biopsy negative groups:

 

  HR for increased mortality
Celiac disease

1.39

Inflammation
(no villous atrophy)

1.72

Latent Celiac
(antibodies but normal mucosa)

1.35

In Sweden only those with celiac disease are treated with a gluten free diet while very few with inflammation or latent disease are. The hypothesis is that the continued consumption has health risks. Note that the study looked at mortality rates but of course this is a marker for overall poorer long term health and increased incidence of chronic disease. Many European countries will only reimburse gluten free foods for those with full celiac disease – these data make the diagnostic situation even less acceptable.

6. CD may be preventable? There is evidence that infant feeding can affect onset of CD. Interesting data from the Swedish epidemic when CD levels went up 3-4-fold during 1984-1996 whereas there was no change in neighbouring countries. The rise in CD coincided with a change in the instructions given to mothers (for which compliance is >90% in Sweden), leading to abrupt gluten introduction and cessation of breast feeding. In 1996 the instructions were changed to encourage longer breast feeding and to introduce gluten gradually between months 4-6 and while still breast feeding – the CD rate dropped 4-fold in the ensuing years (Olsson, 2008; Myléus, 2009).

image

7. A study by Norris et al showed that feeding between 4-6 months was linked to the lowest risk of developing CD (Norris 2005).

image

The combined evidence lead to the ESPGHAN (European Society for Pediatric Gastroenterology, Hepatology, and Nutrition, Agostoni et al 2008) to issue a statement advising avoidance of early (<4 months) and late (>6 months) introduction of gluten, and to do so gradually while still breast feeding. Although the evidence is not from clinical trials, babies have to be fed and a choice needs to be made, in the circumstances the evidence points to this being the best advice (there are some clinical trials in progress or recruiting but they seem to be comparing introduction at 6 months and 12 months, except for 1 Finnish trial which does not specify - clinicaltrials.gov). As always, clinical trials and nutrition is a difficult subject – given the evidence would you want your child to be in the late introduction arm?

Arguments for genetic testing: In newborns it would be helpful to identify the genetically predisposed so that the correct feeding advice can be given (it’s not just celiac disease but other autoimmune diseases as well, with shared HLA alleles). Why test though, why not give the same advice to all? The feeding program needs to be carefully followed and not all populations are as compliant as the Swedish (certainly not the Italians!) so it makes sense to target just the at risk groups, and if we don’t start somewhere we’ll never get to personalised medicine!

Are some people squeamish about the idea of genetically testing newborns for disease risk? It shouldn’t be the case here, there is a clear prevention advantage and in any case, if it were proposed to serologically HLA type them then I bet there would not be protests – it’s genetic exceptionalism…

For older children and adults – at least it can be useful in relatives of CD patients, excluding those who are not predisposed and identifying those who should be screened for auto-antibodies and then the biopsy if necessary. As a general screen? Maybe not an economical test yet for the state or insurers to pay for but it could be encouraged, the statistic that only 10-20% of CD sufferers are diagnosed is highly significant. If the true numbers were correctly diagnosed, and also if the bar was lowered to include antibody positives then all of a sudden there would be 10-20 fold more gluten sensitive individuals and this would have a positive effect on the gluten free food market, prices would drop, choice would increase and the lot of the CD suffer would improve. After all it’s not really necessary for it to be a disease, “just” avoid the gluten. Unfortunately it’s not so easy to do so, gluten is everywhere, and it’s use has increased enormously over the last few decades. It’s used as an ingredient in most processed food, to give texture - I am based in Italy, in a salumeria recently I was choosing some prosciutto, there were two types (actually being Italy there were probably about 20 types, just using licence here) and I asked the difference: one was free of phosphates while the other was also free of lactose and gluten – what the hell was gluten doing in ham in the first place, in Italy of all places?!

Some testing options:

Prometheus have a fairly expensive test at $329
Genelex at even more - $445
Decode and 23andme do not have SNPs that comprehensively type the HLA alleles but do have some other slight risk alleles discovered by GWAS. Not sure about Navigenics and Pathway as I couldn’t find the SNPs on their sites.

A promising recent development was published in PLOS One (Monsuur et al,  2009) where they describe 6 tagging SNPs that comprehensively genotype the relevant HLA alleles – any test based on these SNPs would be a lot cheaper than the PCR based methods used by Prometheus – e.g. 23andme could add them to their scan (as long as there are no exorbitant licence fees since the authors have applied for a patent on the findings … that’s another story for another day…)

Thursday, February 18, 2010

What’s wrong with GWAS?

A paper was published in JAMA a few days ago (Paynter et al, Association Between a Literature-Based Genetic Risk Score and Cardiovascular Events in Women) showing that a genetic score based on 101 CVD related SNPs was not effective as a screening tool. So what happened to the promise of GWAS? One or two SNPs are not enough but we were told that when we get to panels of 30, 40 or more then we would see something real and useful, apparently we are not, so is it over? Is the fate for GWAS that of the candidate gene studies where initial positives were generally shown to be chance?

Maybe not. But maybe this study is proving, just like with candidate gene studies, that it is naïve to think that “blind” association studies of genes with complex diseases will provide useful results – these are diseases where the causes are many-fold involving genetics, behaviour and environment, but where in general just the disease end-point and the genetics are actually measured.

The Paynter paper used a collection of SNPs chosen from the NHGRI database that had an association with either:

“…cardiovascular disease (myocardial infarction [MI], stroke, coronary disease, and/or cardiovascular death) or an intermediate phenotype (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, blood pressure, diabetes, hemoglobin A1c or fasting blood glucose, and high-sensitivity C-reactive protein)…”

Wow, that’s quite a heterogeneous mixture of associations and maybe is one of the problems. They calculated the genetic score and compared it to the endpoint: “incident MI, ischemic stroke, coronary revascularization, and cardiovascular deaths, which were combined to calculate total cardiovascular disease.”

Again, a lot of heterogeneity – are we asking too much? CVD is not just one disease with one cause, it’s a constellation of diseases involving some or all of inflammation, dislipidemia, hypertension, etc. If we took it to the next extreme we could say why not add all of the type 2 diabetes related SNPs and then see if we have a genetic predictor of the disease “cardiovascular diabetes” – and what would that cover, about 60-70% of the population at risk?

So a likely problem is in the initial GWAS studies that use not very precise endpoints to discover “blind” (as in hypothesis free) associations and yield a very imprecise and apparently useless screening tool. Another “problem” is that most of the SNPs are related to intermediate phenotypes (lipid levels, hypertension, inflammation etc) and so of course the genetic score is not going to measure a risk that is “over and above” the contribution of traditional risk factors and family history. The CTFR mutation in cystic fibrosis will not contribute much “over and above” the sweat test as a predictor of the disease – this doesn’t mean that genetics have no value - no help (yet) for CTFR of course but obvious that it would be nice to have a predictor that didn’t actually depend on having raised risk levels).

But apart from the poorly focussed heterogeneous endpoints, and therefore associations, from GWAS, one major missing feature of almost all studies is the effect of environment/behaviour on the associations, generally this means assessing diet and lifestyle, which is very difficult. But is this where some of the “missing” heritablity lies? When you are looking at a disease which affects 40% percent of the population it means that a lot more than 40% will be “genetically” predisposed but did not get the disease because of a healthier lifestyle. This makes finding a control group for the initial GWAS rather tricky – are the healthy controls healthy because they don’t have the risk alleles or because they have different lifestyles/environment? Almost certainly a mixture of both, but one is usually ignored resulting in dampened down low ORs and probably some missed associations.

The other possibility is one which is becoming more fashionable right now – the many rare variants proposal. It’s attractive from a certain point of view – nice to get the multimillion $ grants to buy the latest sequencing technology and play away – but it is still hard to imagine getting the right answer without environment/behaviour assessment.  Smoking is always assessed in cancer studies, it’s much easier to do so and no-one would think of looking for cancers genes without the smoking assessment, so why is it OK with CVD and diabetes?

Of the much maligned candidate gene studies those that have held up have been those where the gene-environment interaction was assessed. A good example is SOD2 rs4880 SNP and breast/prostate cancer. An early publication linked the Ala allele to breast cancer but subsequent publications were contradictory (table 1), however ALL studies which looked at gene + disease + diet gave the same results – Ala allele was linked to increased risk when antioxidant intake was low (table 2).

Table 1. SOD2 Ala-Val allele association with cancer
Ovarian cancer
Ala
Olsen, 2004
Lung cancer
Val
Liu 2004
Lung cancer
Val
Liu 2004
Bladder
Neither
Terry 2005
Breast & prostate
Ala
Taufer, 2005
Breast
Neither
Cebrian, 2006
Breast
Neither
Oestergaard, 2006
Lymphoma
Ala
Lightfoot, 2006
Breast
Neither
Justenhoven, 2008
Brain
Ala
Rajaraman, 2008
Breast meta-anal
Neither
Bag, 2008*
* However, a proper evaluation of this polymorphism with cancer link demands experiments involving large sample size, cross-tabulation of gene-gene, gene-environment interactions (author comment)

Table 2. SOD2 Ala-Val: Gene x Environment association with cancer
Breast
Ala
Ambrosone, 1999
Breast
Ala
Cai, 2004
Prostate
Ala
Li, 2007
Prostate
Ala
Kang, 2007
Prostate
Ala
Mikhak, 2008
Prostate
Ala
Cooper, 2008

So we see with a diabetes panel in a recent publication (Qi et. al., 2009,  Genetic predisposition, Western dietary pattern, and the risk of type 2 diabetes in men) – they used a panel of GWAS SNPs and assessed the impact of diet on the risk score – the high risk score together with poor diet lead to much higher risk ratios:

image

We’re getting quite impatient – at Eurogene we would like to start using effective panels. The commercial offerings are interesting but not really that useful in the clinic, at least for our needs. We are looking forward to GWAS studies with precise goals (narrowly defined end points) which take into consideration lifestyle/environment and will lead to useful tools because of course by establishing the gene-environment interactions it is much easier to understand what are the risk-lowering interventions – much more useful than just to be told you have a higher risk of heart disease or diabetes. These studies WILL lead to genetic predictive tools that will be useful in clinical decision making, especially for prevention.  I’m confident they will be coming along also because I know that one of the groups actively researching this area is that of Jose Ordovas and Larry Parnell from Tufts – a group that has discovered (and continues to discover/confirm) many gene-environment associations in candidate genes which have stood the test of time. They are already starting to publish and I’m sure many more will be coming (no pressure then Larry!) – keep up with the news on twitter and via Larry’s blog (@larry_parnell and “Variable Genome”)

Thursday, February 11, 2010

Personal Genetics - Code of Practice

This blog is about personal genetics and disease prevention - the EUROGENE eTEN project was set up and funded by the EU to establish the infrastructure to deliver personal genetics services via practitioner or direct to consumer.

The aim of the blog will be to report on progress of the project and comment on relevant research / developments in related areas. One of the tasks of the project was a review of the European regulatory framework - this has been completed and will be summarised in a later blog (the full review has also been submitted for publication.

The main finding is the absence of formal regulations in place now and the probability that this unclear situation will not change for some time. Meanwhile personal genetics services roar ahead, with prices falling and genome coverage increasing. Our opinion is that we should follow and promote the Industry Code of Practice proposed by the UK Human Genetics Commission (HGC). This code was developed by academics, regulators, industry members and medical stakeholders to cover all aspects including testing, marketing, customer support, quality of information. In the absence of formal regulation we welcome the code and feel very strongly that the customer (both the practitioner and the end-user) should be fully informed about all aspects of the genetic testing services and all information should be easily available online. The first thing that any potential user of a genetic test, is full disclosure and transparency and we also feel that all companies should protect both the industry and consumers by following the HGC guidelines

“Common Framework of Principles for direct-to-consumer genetic testing services”

Claims must be accurate (promotional and technical), evidence transparent
• Genetic variants tested must have been clinically validated
• Risk assessments must use accepted methods and be transparent
• Clarity on privacy and use of customer’s DNA
• Full and clear information for the customer to understand the test including accuracy and limitations
• Recommendations to purchase follow-on products (e.g. supplements) must be fully and transparently supported by scientific evidence
• For some tests professional genetic and medical help should be available if needed
• Tests should not be supplied DTC to adults unable to provide informed consent