Of Mice and Men Again: New Genomic Study Helps Explain why Mouse Models of Acute Inflammation do not Work in Men

25 02 2013

ResearchBlogging.org

This post is update after a discussion at Twitter with @animalevidence who pointed me at a great blog post at Speaking of Research ([19], a repost of [20], highlighting the shortcomings of the current study using just one single inbred strain of mice (C57Bl6)  [2013-02-26]. Main changes are in blue

A recent paper published in PNAS [1] caused quite a stir both inside and outside the scientific community. The study challenges the validity of using mouse models to test what works as a treatment in humans. At least this is what many online news sources seem to conclude: “drug testing may be a waste of time”[2], “we are not mice” [3, 4], or a bit more to the point: mouse models of inflammation are worthless [5, 6, 7].

But basically the current study looks only at one specific area, the area of inflammatory responses that occur in critically ill patients after severe trauma and burns (SIRS, Systemic Inflammatory Response Syndrome). In these patients a storm of events may eventually lead to organ failure and death. It is similar to what may occur after sepsis (but here the cause is a systemic infection).

Furthermore the study only uses one single approach: it compares the gene response patterns in serious human injuries (burns, trauma) and a human model partially mimicking these inflammatory diseases (human healthy volunteers receiving  a low dose endotoxin) with the corresponding three animal models (burns, trauma, endotoxin).

And, as highlighted by Bill Barrington of “Understand Nutrition” [8], the researchers have only tested the gene profiles in one single strain of mice: C57Bl6 (B6 for short). If B6 was the only model used in practice this would be less of a problem. But according to Mark Wanner of the Jackson Laboratory [19, 20]:

 It is now well known that some inbred mouse strains, such as the C57BL/6J (B6 for short) strain used, are resistant to septic shock. Other strains, such as BALB and A/J, are much more susceptible, however. So use of a single strain will not provide representative results.

The results in itself are very clear. The figures show at a glance that there is no correlation whatsoever between the human and B6 mouse expression data.

Seok and 36 other researchers from across the USA  looked at approximately 5500 human genes and their mouse analogs. In humans, burns and traumatic injuries (and to a certain extent the human endotoxin model) triggered the activation of a vast number of genes, that were not triggered in the present C57Bl6 mouse models. In addition the genomic response is longer lasting in human injuries. Furthermore, the top 5 most activated and most suppressed pathways in human burns and trauma had no correlates in mice. Finally, analysis of existing data in the Gene Expression (GEO) Database showed that the lack of correlation between mouse and human studies was also true for other acute inflammatory responses, like sepsis and acute infection.

This is a high quality study with interesting results. However, the results are not as groundbreaking as some media suggest.

As discussed by the authors [1], mice are known to be far more resilient to inflammatory challenge than humans*: a million fold higher dose of endotoxin than the dose causing shock in humans is lethal to mice.* This, and the fact that “none of the 150  candidate agents that progressed to human trials has proved successful in critically ill patients” already indicates that the current approach fails.

[This is not entirely correct the endotoxin/LPS dose in mice is 1000–10,000 times the dose required to induce severe disease with shock in humans [20] and mice that are resilient to endotoxin may still be susceptible to infection. It may well be that the endotoxin response is not a good model for the late effects of  sepsis]

The disappointing trial results have forced many researchers to question not only the usefulness of the current mouse models for acute inflammation [9,10; refs from 11], but also to rethink the key aspects of the human response itself and the way these clinical trials are performed [12, 13, 14]. For instance, emphasis has always been on the exuberant inflammatory reaction, but the subsequent immunosuppression may also be a major contributor to the disease. There is also substantial heterogeneity among patients [13-14] that may explain why some patients have a good prognosis and others haven’t. And some of the initially positive results in human trials have not been reproduced in later studies either (benefit of intense glucose control and corticosteroid treatment) [12]. Thus is it fair to blame only the mouse studies?

dick mouse

dick mouse (Photo credit: Wikipedia)

The coverage by some media is grist to the mill of people who think animal studies are worthless anyway. But one cannot extrapolate these findings to other diseases. Furthermore, as referred to above, the researchers have only tested the gene profiles in one single strain of mice: C57Bl6, meaning that “The findings of Seok et al. are solely applicable to the B6 strain of mice in the three models of inflammation they tested. They unduly generalize these findings to mouse models of inflammation in general. [8]“

It is true that animal studies, including rodent studies, have their limitations. But what are the alternatives? In vitro studies are often even more artificial, and direct clinical testing of new compounds in humans is not ethical.

Obviously, the final proof of effectiveness and safety of new treatments can only be established in human trials. No one will question that.

A lot can be said about why animal studies often fail to directly translate to the clinic [15]. Clinical disparities between the animal models and the clinical trials testing the treatment (like in sepsis) are one reason. Other important reasons may be methodological flaws in animal studies (i.e. no randomization, wrong statistics) and publication bias: non-publication of “negative” results appears to be prevalent in laboratory animal research.[15-16]. Despite their shortcomings, animal studies and in vitro studies offer a way to examine certain aspects of a process, disease or treatment.

In summary, this study confirms that the existing (C57Bl6) mouse model doesn’t resemble the human situation in the systemic response following acute traumatic injury or sepsis: the genomic response is entirely different, in magnitude, duration and types of changes in expression.

The findings are not new: the shortcomings of the mouse model(s) were long known. It remains enigmatic why the researchers chose only one inbred strain of mice, and of all mice only the B6-strain, which is less sensitive to endotoxin, and only develop acute kidney injury (part of organ failure) at old age (young mice were used) [21]. In this paper from 2009 (!) various reasons are given why the animal models didn’t properly mimic the human disease and how this can be improved. The authors stress that:

the genetically heterogeneous human population should be more accurately represented by outbred mice, reducing the bias found in inbred strains that might contain or lack recessive disease susceptibility loci, depending on selective pressures.” 

Both Bill Barrington [8] and Mark Wanner [18,19] propose the use of “diversity outbred cross or collaborative cross mice that  provide additional diversity.” Indeed, “replicating genetic heterogeneity and critical clinical risk factors such as advanced age and comorbid conditions (..) led to improved models of sepsis and sepsis-induced AKI (acute kidney injury). 

The authors of the PNAS paper suggest that genomic analysis can aid further in revealing which genes play a role in the perturbed immune response in acute inflammation, but it remains to be seen whether this will ultimately lead to effective treatments of sepsis and other forms of acute inflammation.

It also remains to be seen whether comprehensive genomic characterization will be useful in other disease models. The authors suggest for instance,  that genetic profiling may serve as a guide to develop animal models. A shotgun analyses of gene expression of thousands of genes was useful in the present situation, because “the severe inflammatory stress produced a genomic storm affecting all major cellular functions and pathways in humans which led to sufficient perturbations to allow comparisons between the genes in the human conditions and their analogs in the murine models”. But rough analysis of overall expression profiles may give little insight in the usefulness of other animal models, where genetic responses are more subtle.

And predicting what will happen is far less easy that to confirm what is already known….

NOTE: as said the coverage in news and blogs is again quite biased. The conclusion of a generally good Dutch science  news site (the headline and lead suggested that animal models of immune diseases are crap [6]) was adapted after a critical discussion at Twitter (see here and here), and a link was added to this blog post). I wished this occurred more often….
In my opinion the most balanced summaries can be found at the science-based blogs: ScienceBased Medicine [11] and NIH’s Director’s Blog [17], whereas “Understand Nutrition” [8] has an original point of view, which is further elaborated by Mark Wanner at Speaking of Research [19] and Genetics and your health Blog [20]

References

  1. Seok, J., Warren, H., Cuenca, A., Mindrinos, M., Baker, H., Xu, W., Richards, D., McDonald-Smith, G., Gao, H., Hennessy, L., Finnerty, C., Lopez, C., Honari, S., Moore, E., Minei, J., Cuschieri, J., Bankey, P., Johnson, J., Sperry, J., Nathens, A., Billiar, T., West, M., Jeschke, M., Klein, M., Gamelli, R., Gibran, N., Brownstein, B., Miller-Graziano, C., Calvano, S., Mason, P., Cobb, J., Rahme, L., Lowry, S., Maier, R., Moldawer, L., Herndon, D., Davis, R., Xiao, W., Tompkins, R., , ., Abouhamze, A., Balis, U., Camp, D., De, A., Harbrecht, B., Hayden, D., Kaushal, A., O’Keefe, G., Kotz, K., Qian, W., Schoenfeld, D., Shapiro, M., Silver, G., Smith, R., Storey, J., Tibshirani, R., Toner, M., Wilhelmy, J., Wispelwey, B., & Wong, W. (2013). Genomic responses in mouse models poorly mimic human inflammatory diseases Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1222878110
  2. Drug Testing In Mice May Be a Waste of Time, Researchers Warn 2013-02-12 (science.slashdot.org)
  3. Susan M Love We are not mice 2013-02-14 (Huffingtonpost.com)
  4. Elbert Chu  This Is Why It’s A Mistake To Cure Mice Instead Of Humans 2012-12-20(richarddawkins.net)
  5. Derek Low. Mouse Models of Inflammation Are Basically Worthless. Now We Know. 2013-02-12 (pipeline.corante.com)
  6. Elmar Veerman. Waardeloos onderzoek. Proeven met muizen zeggen vrijwel niets over ontstekingen bij mensen. 2013-02-12 (wetenschap24.nl)
  7. Gina Kolata. Mice Fall Short as Test Subjects for Humans’ Deadly Ills. 2013-02-12 (nytimes.com)

  8. Bill Barrington. Are Mice Reliable Models for Human Disease Studies? 2013-02-14 (understandnutrition.com)
  9. Raven, K. (2012). Rodent models of sepsis found shockingly lacking Nature Medicine, 18 (7), 998-998 DOI: 10.1038/nm0712-998a
  10. Nemzek JA, Hugunin KM, & Opp MR (2008). Modeling sepsis in the laboratory: merging sound science with animal well-being. Comparative medicine, 58 (2), 120-8 PMID: 18524169
  11. Steven Novella. Mouse Model of Sepsis Challenged 2013-02-13 (http://www.sciencebasedmedicine.org/index.php/mouse-model-of-sepsis-challenged/)
  12. Wiersinga WJ (2011). Current insights in sepsis: from pathogenesis to new treatment targets. Current opinion in critical care, 17 (5), 480-6 PMID: 21900767
  13. Khamsi R (2012). Execution of sepsis trials needs an overhaul, experts say. Nature medicine, 18 (7), 998-9 PMID: 22772540
  14. Hotchkiss RS, Coopersmith CM, McDunn JE, & Ferguson TA (2009). The sepsis seesaw: tilting toward immunosuppression. Nature medicine, 15 (5), 496-7 PMID: 19424209
  15. van der Worp, H., Howells, D., Sena, E., Porritt, M., Rewell, S., O’Collins, V., & Macleod, M. (2010). Can Animal Models of Disease Reliably Inform Human Studies? PLoS Medicine, 7 (3) DOI: 10.1371/journal.pmed.1000245
  16. ter Riet, G., Korevaar, D., Leenaars, M., Sterk, P., Van Noorden, C., Bouter, L., Lutter, R., Elferink, R., & Hooft, L. (2012). Publication Bias in Laboratory Animal Research: A Survey on Magnitude, Drivers, Consequences and Potential Solutions PLoS ONE, 7 (9) DOI: 10.1371/journal.pone.0043404
  17. Dr. Francis Collins. Of Mice, Men and Medicine 2013-02-19 (directorsblog.nih.gov)
  18. Tom/ Mark Wanner Why mice may succeed in research when a single mouse falls short (2013-02-15) (speakingofresearch.com) [repost, with introduction]
  19. Mark Wanner Why mice may succeed in research when a single mouse falls short (2013-02-13/) (http://community.jax.org) %5Boriginal post]
  20. Warren, H. (2009). Editorial: Mouse models to study sepsis syndrome in humans Journal of Leukocyte Biology, 86 (2), 199-201 DOI: 10.1189/jlb.0309210
  21. Doi, K., Leelahavanichkul, A., Yuen, P., & Star, R. (2009). Animal models of sepsis and sepsis-induced kidney injury Journal of Clinical Investigation, 119 (10), 2868-2878 DOI: 10.1172/JCI39421




What Did Deep DNA Sequencing of Traditional Chinese Medicines (TCMs) Really Reveal?

30 04 2012

ResearchBlogging.orgA recent study published in PLOS genetics[1] on a genetic audit of Traditional Chinese Medicines (TCMs) was widely covered in the news. The headlines are a bit confusing as they said different things. Some headlines say “Dangers of Chinese Medicine Brought to Light by DNA Studies“, others that Bear and Antelope DNA are Found in Traditional Chinese Medicine, and still others more neutrally: Breaking down traditional Chinese medicine.

What have Bunce and his group really done and what is the newsworthiness of this article?

doi:info:doi/10.1371/journal.pgen.1002657.g001

Photos from 4 TCM samples used in this study doi/10.1371/journal.pgen.1002657.g001

The researchers from the the Murdoch University, Australia,  have applied Second Generation, high-throughput sequencing to identify the plant and animal composition of 28 TCM samples (see Fig.). These TCM samples had been seized by Australian Customs and Border Protection Service at airports and seaports across Australia, because they contravened Australia’s international wildlife trade laws (Part 13A EPBC Act 1999).

Using primers specific for the plastid trnL gene (plants) and the mitochondrial 16S ribosomal RNA (animals), DNA of sufficient quality was obtained from 15 of the 28 (54%) TCM samples. The resultant 49,000 amplicons (amplified sequences) were analyzed by high-throughput sequencing and compared to reference databases.

Due to better GenBank coverage, the analysis of vertebrate DNA was simpler and less ambiguous than the analysis of the plant origins.

Four TCM samples – Saiga Antelope Horn powder, Bear Bile powder, powder in box with bear outline and Chu Pak Hou Tsao San powder were found to contain DNA from known CITES- (Convention on International Trade in Endangered Species) listed species. This is no real surprise, as the packages were labeled as such.

On the other hand some TCM samples, like the “100% pure” Saiga Antilope powder, were “diluted” with  DNA from bovids (i.e. goats and sheep), deer and/or toads. In 78% of the samples, animal DNA was identified that had not been clearly labeled as such on the packaging.

In total 68 different plant families were detected in the medicines. Some of the TCMs contained plants of potentially toxic genera like Ephedra and Asarum. Ephedra contains the sympathomimetic ephedrine, which has led to many, sometimes fatal, intoxications, also in Western countries. It should be noted however, that pharmacological activity cannot be demonstrated by DNA-analysis. Similarly, certain species of Asarum (wild ginger) contain the nephrotoxic and carcinogenic aristolochic acid, but it would require further testing to establish the presence of aristolochia acid in the samples positive for Asarum. Plant DNA assigned to other potentially toxic, allergic (nuts, soy) and/or subject to CITES regulation were also recovered. Again, other gene regions would need to be targeted, to reveal the exact species involved.

Most newspapers emphasized that the study has brought to light “the dangers of TCM”

For this reason The Telegraph interviewed an expert in the field, Edzard Ernst, Professor of Complementary Medicine at the University of Exeter. Ernst:

“The risks of Chinese herbal medicine are numerous: firstly, the herbs themselves can be toxic; secondly, they might interact with prescription drugs; thirdly, they are often contaminated with heavy metals; fourthly, they are frequently adulterated with prescription drugs; fifthly, the practitioners are often not well trained, make unsubstantiated claims and give irresponsible, dangerous advice to their patients.”

Ernst is right about the risks. However, these adverse effects of TCM have long been known. Fifteen years ago I happened to have written a bibliography about “adverse effects of herbal medicines*” (in Dutch, a good book on this topic is [2]). I did exclude interactions with prescription drugs, contamination with heavy metals and adulteration with prescription drugs, because the events (publications in PubMed and EMBASE) were to numerous(!). Toxic Chinese herbs mostly caused acute toxicity by aconitine, anticholinergic (datura, atropa) and podophyllotoxin intoxications. In Belgium 80 young women got nephropathy (kidney problems) after attending a “slimming” clinic because of mixup of Stephania (chinese: fangji) with Aristolochia fanghi (which contains the toxic aristolochic acid). Some of the women later developed urinary tract cancer.

In other words, toxic side effects of herbs including chinese herbs are long known. And the same is true for the presence of (traces of) endangered species in TCM.

In a media release the complementary health council (CHC) of Australia emphasized that the 15 TCM products featured in this study were rogue products seized by Customs as they were found to contain prohibited and undeclared ingredients. The CHC emphasizes the proficiency of rigorous regulatory regime around complementary medicines, i.e. all ingredients used in listed products must be on the permitted list of ingredients. However, Australian regulations do not apply to products purchased online from overseas.

Thus if the findings are not new and (perhaps) not applicable to most legal TCM, then what is the value of this paper?

The new aspect is the high throughput DNA sequencing approach, which allows determination of a larger number of animal and plant taxa than would have been possible through morphological and/or biochemical means. Various TCM-samples are suitable: powders, tablets, capsules, flakes and herbal teas.

There are also some limitations:

  1. DNA of sufficient quality could only be obtained from appr. half of the samples.
  2. Plants sequences could often not be resolved beyond the family level. Therefore it could often not be established whether an endangered of toxic species was really present (or an innocent family member).
  3. Only DNA sequences can be determined, not pharmacological activity.
  4. The method is at best semi-quantitative.
  5. Only plant and animal ingredients are determined, not contaminating heavy metals or prescription drugs.

In the future, species assignment (2) can be improved with the development of better reference databases involving multiple genes and (3) can be solved by combining genetic (sequencing) and metabolomic (for compound detection) approaches. According to the authors this may be a cost-effective way to audit TCM products.

Non-technical approaches may be equally important: like convincing consumers not to use medicines containing animal traces (not to speak of  endangered species), not to order  TCM online and to avoid the use of complex, uncontrolled TCM-mixes.

Furthermore, there should be more info on what works and what doesn’t.

*including but not limited to TCM

References

  1. Coghlan ML, Haile J, Houston J, Murray DC, White NE, Moolhuijzen P, Bellgard MI, & Bunce M (2012). Deep Sequencing of Plant and Animal DNA Contained within Traditional Chinese Medicines Reveals Legality Issues and Health Safety Concerns. PLoS genetics, 8 (4) PMID: 22511890 (Free Full Text)
  2. Adverse Effects of Herbal Drugs 2 P. A. G. M. De Smet K. Keller R. Hansel R. F. Chandler, Paperback. Springer 1993-01-15. ISBN 0387558004 / 0-387-55800-4 EAN 9780387558004
  3. DNA may weed out toxic Chinese medicine (abc.net.au)
  4. Bedreigde beren in potje Lucas Brouwers, NRC Wetenschap 14 april 2012, bl 3 [Dutch]
  5. Dangers in herbal medicine (continued) – DNA sequencing to hunt illegal ingredients (somethingaboutscience.wordpress.com)
  6. Breaking down traditional Chinese medicine. (green.blogs.nytimes.com)
  7. Dangers of Chinese Medicine Brought to Light by DNA Studies (news.sciencemag.org)
  8. Chinese herbal medicines contained toxic mix (cbc.ca)
  9. Screen uncovers hidden ingredients of Chinese medicine (Nature News)
  10. Media release: CHC emphasises proficiency of rigorous regulatory regime around complementary medicines (http://www.chc.org.au/)




FDA to Regulate Genetic Testing by DTC-Companies Like 23andMe

14 06 2010

Direct-to-consumer (DTC) genetic testing refers to genetic tests that are marketed directly to consumers via television, print advertisements, or the Internet. This form of testing, which is also known as at-home genetic testing, provides access to a person’s genetic information without necessarily involving a doctor or insurance company in the process. [definition from NLM's Genetic Home Reference Handbook]

Almost two years ago I wrote about 23andMe (23andMe: 23notMe, not yet),  a well known DTC company, that offers a genetics scan (SNP-genotyping) to the public ‘for research’, ‘for education’ and ‘for fun’:

“Formally 23andMe denies there is a diagnostic purpose (in part, surely, because the company doesn’t want to antagonize the FDA, which strictly regulates diagnostic testing for disease). However, 23andme does give information on your risk profile for certain diseases, including Parkinson”

In another post Personalized Genetics: Too Soon, Too Little? I summarized an editorial by Ioannides on the topic. His (and my) conclusion was that “the promise of personalized genetic prediction may be exaggerated and premature”. The most important issue is that predictive power to individualize risks is relatively weak. Ioannidis emphasized that despite the poor evidence, direct to consumer genetic testing has already begun and is here to stay. He proposed several safeguards, including transparent and thorough reporting, unbiased continuous synthesis and grading of the evidence and alerting the public that most genetic tests have not yet been shown to be clinically useful.

And now these “precautionary measures” actually seem to happen.
Last week the FDA sent 5 DTC-companies, including 23andMe a letter saying “their tests are medical devices that must receive regulatory approval before they can be marketed.” (ie. see NY-times article).

Alberto Gutierrez, who leads diagnostic test regulation at the FDA, wrote in the letters:

“Premarket review allows for an independent and unbiased assessment of a diagnostic test’s ability to generate test results that can reliably be used to support good health care decisions,”

These letters are part of an initiative to better explain the FDA’s actions by providing information that supports clinical medicine, biomedical innovation, and public health,” (May 19 New England Journal of Medicine commentary, source: see AMED-news)

Although it doesn’t look like the tests will be taken from the market, 23andMe does take a quite a rebellious attitude: one of its directors called the FDA “appallingly paternalistic.”

Many support this view: “people have the right to know their own genetic make-up”, so to say. Furthermore as discussed above, 23andMe denies that their genetic scans are meant for diagnosis.

In my view the latter is largely untrue. At least 23andMe suggests that knowing a scan does tell you something about your risks for certain diseases.
However, the risks are often not that straightforward. You just can’t “measure” the risk of a multifactorial disease like diabetes by “scanning” a few weakly predisposing  genes. Often the results are given in relative risk, which is highly confusing. In her TED-talk the 23andMe director Anne Wojcicki said her husband Sergey Brin (Google), had a 50% chance of getting Parkinson, but his relative risk (RR, based on the LRRK2-mutation, which isn’t the most crucial gene for getting Parkinson) varies from 20% to 80% , which means that this mutation increases his absolute risk of getting Parkinson from 2-5% (normal chance) to 4-10% at the most. (see this post).

Furthermore, as reported by Venture in Nature (October 8, 2009): For seven diseases, 50% or less of the predictions of two companies agreed across five individuals (i.e. for one disease: 23andMe : RR 4.02, and Navigenics RR: 1.25). On the other hand *fun* diagnoses could lead to serious concern in, or wrong/unnecessary decisions (removal of ovaries, changing drug doses) by patients.

There are also concerns with regard to their good-practice standards, as 23andMe just flipped a 96-wells plate of costumer DNA (see Genetic Future for a balanced post), which upset a mother noticing that her son didn’t have compatible genes. But lets assume that proper precautions will prevent this to happen again.

There are also positive aspects: results of a preliminary study showed that people who find out they have high genetic risk for cardiovascular disease are more likely to change their diet and exercise patterns than are those who learn they have a high risk from family history. (Technology ReviewGenetic Testing Can Change Behavior).

Furthermore, people buy those tests themselves and, indeed, there genes are their own.

However, I agree with Dr. Gutierrez of the FDA saying: “We really don’t have any issues with denying people information. We just want to make sure the information they are given is correct. (NY-Times). The FDA is putting the consumers first.

However, it will be very difficult to be consistent. What about total body scans in normal healthy people, detecting innocent incidentilomas? Or what about the controversial XMRV-tests offered by the Whittemore Peterson Institute (WPI) directly to CFS- patients? (see these posts) And one step further (although not in the diagnostic field): the ineffective CAM/homeopathic products sold over the counter?

I wouldn’t mind if these tests/products would be held up to the light. Consumers should not be misled by the results of unproven or invalid tests, and where needed should be offered the guidance of a healthcare provider.

But if tests are valid and risk predictions correct, it is up to the “consumer” if he/she wants to purchase such a test.

—————–

What Five FDA Letters Mean for the Future of DTC Genetic Testingat Genomics law Report is highly recommendable, but couldn’t be accessed while writing the post.

[Added: 2010-06-14 13.10]

  • Problem assessing Genomics Law Report is resolved.
  • Also recommendable: the post “FDA to regulate genetic tests as “devices”” at PHG Foundation. This post highlights that simply trying to classify the complete genomic testing service as “a device” is inadequate and will not address the difficult issues at hand. One of the biggest issues is that, while classifying DTC genetics tests as devices is certainly appropriate for assessing their analytical validity and direct safety, it does not and cannot provide an assessment of the service, thus of the predictions and interpretations resulting from the genome scans.  Although standard medical testing has traditionally been overseen by professional medical bodies, the current genomic risk profiling tests are simply not good enough to be used by health care services. (see post)
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Personalized Genetics: Too Soon, Too Little?

9 02 2009

ResearchBlogging.orgPersonalized Medicine is the concept that managing patient’s health should be based on the individual patient’s specific characteristics instead of on the standards of care. Often the term ‘personalized medicine’ is restricted to the use of information about a patient’s genotype or gene expression profile to further tailor medical care to an individual’s needs (see [1])

This so called Personalized Genetics is a beautiful concept. Suppose you could predict people’s risk for a certain disease and be able to prevent it by encouraging positive lifestyle changes and/or start a tailor made therapy, suppose you could predict which patients would respond to an intervention and which people should avoid certain medications. Wouldn’t that be wonderful and much better than treating everybody the same way only to benefit a few?

Research like the human genome project and recent advances in genomics research have boosted progress in the discovery of susceptibility genes and fueled expectations about opportunities of genetic profiling for personalizing.

But are the high expectations justified?

For personalized genetics to be (clinically) effective it must fulfill the following requirements (based on [2]):

  1. Clear and strong association of the gene (expression) variant with the susceptibility to a disease or the outcome of a treatment
  2. Improved prediction compared to other risk factors, including traditional risk factors and clinical judgment…
  3. ..as determined in good quality studies with a sufficient number of events (if the events are rare you cannot accurately predict the outcome)
    (1-3 make up the predictive performance)
  4. The availability of effective interventions or effective alternatives
  5. Cost-effectiveness

    dna-cubes50-berci

According to an editorial in the January issue of the Annals of Internal Medicine “the promise of personalized genetic prediction may be exaggerated and premature” [2]. This is especially true for many complex diseases, where 1 variant alone is unlikely to make the difference.

The editorial is written by John Ioannidis, who is a professor at the University of Ioannina School of Medicine in Greece and has an adjunct appointment at Tufts University School of Medicine in Boston. His research focuses on meta-analysis and evidence-based medicine with special emphasis on research methodology. Ioannidis is a brilliant researcher, epidemiologist and inspiring lecturer (I have attended a lecture of him once at a Cochrane Colloquium). Therefore I would urge everyone interested in personalize genetics to read his editorial.

Here I will give a summary of the editorial entitled “Personalized genetic prediction: too limited, too expensive, or too soon” [2].The editorial summarizes two publications in the same issue of the journal [3,4] and gives an overview of the literature.

Ioannidis stresses that recent studies into the predictive performance of common genetic traits have several shortcomings, including an often weak design with few events (*3)*, incomplete comparison with traditional risk factors (*2) and exaggerated prediction of effects because of the models used (*1).

To date, the genotypic information does not substantially improve the prediction of future cardiovascular disease (CVD), prostate cancer and type 2 diabetes beyond traditional risk factors. In the case of age-related macular degeneration, genetic information does increase the ability to predict progression to the disease. However the predictive power to individualize risks remains relatively weak.

Indeed, a recent paper published in PLOS [5] reinforces that a strong association between single nucleotide polymorphisms (SNPs) and a multifactorial disease like age-related macular degeneration, diabetes type 2, CVD and Crohn disease may be very valuable for establishing etiological hypotheses, but do not guarantee effective discrimination between cases and controls and are therefore of little clinical value yet. For further details with regard to the methods used to determine clinical validity of genetic testing you are encouraged to read the entire (free) paper [5].

Likewise, the study of Paynter et al [3] reviewed by Ioannidis, shows that genetic variation in chromosome 9p21.3 (rs10757274) was strongly and consistently associated with incident CVD in a cohort of white women, but did not improve on the discrimination or classification of predicted risk achieved with traditional risk factors, high-sensitivity C-reactive protein, and family history of premature myocardial infarction. Thus “knowing a patient’s rs10757274 genotype would not help a clinician make better preventive or therapeutic decisions to reduce future risk for heart disease”.
This holds also true for many other potentially causal single SNPs: they have a relatively small effect on their own. Complex diseases are probably the result of numerous gene-gene and gene-environment interactions, which may differ from one population to the other and only explain a small proportion of the trait variance.

Even improved prediction (*1-3) does not necessarily make a predictive test useful. The prevalence of the disease is also an important determinant, i.e. people with high risk gene variants for a rare disease may have a significant higher-than average risk, but still a negligible probability of developing the disease.

Clinical utility of the genetic prediction also depends on the availability of effective interventions (*4) and the cost effectiveness (*5). Another paper in the same Ann. Intern. Med. issue [4] shows that although CYP2C9 and VKORC1 strongly predict the chance of bleeding as a side effect of warfarin treatment, genotype-guided dosing appeared not to be cost-effective for patients requiring initiation of warfarin therapy. Piquant detail: The FDA has approved this kind of genetic testing, although there is no good evidence that such genotyping does in fact reduce the risk of hemorrhage in everyday clinical practice. Such knowledge would require large well designed RCT’s.

Ioannidis emphasizes that despite the poor evidence, genetic testing and commercial use (direct to consumer genetic testing) have already begun and are here to stay. He proposes several safeguards, including transparent and thorough reporting, unbiased continuous synthesis and grading of the evidence and alerting the public that most genetic tests have not yet been shown to be clinically useful. He concludes the editorial as follows:

Helping patients and physicians to decide when to do genetic tests will be a tough task because neither knows much about the rapidly emerging field of genomics. We need to learn more about what our genome can tell us and, more important, what it cannot tell us.

* refers to list, points 1-5

SOURCES and FURTHER READING

1. http://en.wikipedia.org/wiki/Personalized_medicine
2: Ioannidis JP. (2009). Personalized genetic prediction: too limited, too expensive, or too soon? Ann Intern Med, 150 (2), 139-141 DOI: 19153414 {=wrong DOI researchblogs click here to be linked to PubMed)
3: Paynter NP, Chasman DI, Buring JE, Shiffman D, Cook NR, Ridker PM. Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. Ann Intern Med. 2009 Jan 20;150(2):65-72.
4: Eckman MH, Rosand J, Greenberg SM, Gage BF. Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med. 2009 Jan 20;150(2):73-83.
5: Jakobsdottir J, Gorin MB, Conley YP, Ferrell RE, Weeks DE. Interpretation of genetic association studies: markers with replicated highly
significant odds ratios may be poor classifiers. PLoS Genet. 2009 Feb;5(2):e1000337. Epub 2009 Feb 6 (free full text).

6: Janssens AC, van Duijn CM. Genome-based prediction of common diseases: advances and prospects. Hum Mol Genet. 2008 Oct 15;17(R2):R166-73. Review.

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