Oedipus's dilemma

I love Greek mythology, and of all myths, Oedipus is probably the one that fascinates me the most. Nothing to do with the fact that it's become a psychiatric hallmark. I love this myth because it always makes me wonder: if somebody came to you and told you they knew with absolute certainty your future (how many years you'll live, what you'll accomplish, etc.), would you want to know? It's a paradox, because that knowledge would affect the future course of action you choose. Think about Laius: he fulfilled his destiny exactly because of the actions he took in order to avoid his destiny. Predestination paradoxes have been used forever in all mythologies, and even these days -- can you think of at least a novel or a movie where it's been used?

I'm rambling, but I actually have a point for this post, I promise.

As you know, nobody's going to come and offer to tell you your exact destiny. But, they might offer to type your entire genome. And from that, they may argue they can tell you the exact risk you have of developing certain diseases. In fact, some of you may already have opted to have their entire genome typed. Such services have become more affordable, accurate, and efficient in just a handful of years. The benefits are numerous: drug therapy could be genetically targeted, and just by looking at your DNA your doctor could already know which drugs will be more effective and which could instead have adverse effects. Assessing one's risk for cancer, diabetes, or other diseases can be a good motivator to a healthier lifestyle and open up preventive treatment choices.

So, where's the catch?

The catch is that, as a new study on Science Translational Medicine shows [1], sequencing the entire genome doesn't tell us the whole story. In fact, in many cases, it doesn't tell us much at all.

Roberts et al. argue that the risk we need to be able to assess should be pretty strong in order to make preventive measures effective. For example, currently the general population risk of developing breast cancer within a woman's lifetime is 12%, obviously too low for women to opt for a preventive mastectomy. However, if a woman learned that her risk was 90%, she might reconsider. Any preventive measure carries consequences, and therefore, the risk reduction it ensures should be pretty strong in order to establish clinical utility.

After setting a meaningful risk threshold, Roberts et al. collected genetic data from numerous homozygous twin registries and cohorts. (Little pet peeve of mine: couldn't find the exact number of pairs they had in the study, it's probably in the supplemental material, but I find sample size important enough to expect it in the main text). They then developed a mathematical model to estimate the maximum capacity of whole-genome sequencing to predict the risk for 24 common diseases, including autoimmune diseases, cancer, cardiovascular diseases, genito-urinary diseases, neurological diseases, and obesity-associated diseases. The idea behind the mathematical model is to assess the risk increment of an individual with a disease-associated genotype compared to someone with no genetic risk at all. Since homozygous twins have nearly identical genomes, you would expect their genetic risks to have a nearly identical outcome.

"The general public does not appear to be aware that, despite their very similar height and appearance, monozygotic twins in general do not always develop or die from the same maladies. This basic observation, that monozygotic twins of a pair are not always afflicted by the same maladies, combined with extensive epidemiologic studies of twins and statistical modeling, allows us to estimate upper and lower bounds of the predictive value of whole-genome sequencing."

Using their model, the researchers showed that most individuals would show a risk predisposition to at least one of the 24 diseases tested. At the same time, they would test negative for most diseases. What does this mean? It means that we cannot predict the risk allele distribution of the actual population, and most often genetic testing will only say that individual X has the same risk of developing disease Y as the general population -- hardly enough to make whole genome testing surpass the clinical utility threshold.

"Thus, our results suggest that genetic testing, at its best, will not be the dominant determinant of patient care and will not be a substitute for preventative medicine strategies incorporating routine checkups and risk management based on the history, physical status, and life-style of the patient."

[1] Nicholas J. Roberts, Joshua T. Vogelstein, Giovanni Parmigiani, Kenneth W. Kinzler, Bert Vogelstein1 and, & Victor E. Velculescu (2012). The Predictive Capacity of Personal Genome Sequencing Sci Transl Med 4, 133ra58 DOI: 10.1126/scitranslmed.3003380

Having kids wears you out? Same holds for telomeres. In zebra finches.

One of my most popular posts on the blog has been The Immortality Paradox, in which I discuss telomeres, aging, and cancer. Telomeres are the ends of he chromosomes, a bit of non-coding DNA that naturally wears off as cells divide and as we age. Once the telomeres reach a certain critical length the cell stops dividing and eventually dies. As a consequence, telomeres length varies across age groups but, even within the same age group, it varies from individual to individual. So, it becomes natural to ask: is this variation in telomeres length correlated to longevity?

A new study published in PNAS [1] seems to indicate that it is. Now, my personal disclaimer is that I'm always a little skeptical about associations with longevity because there are so many factors and confounders that it's really hard to extrapolate meaningful p-values. However, this study was done in birds (Taeniopygia guttata, or zebra finches), which makes it less prone to bias than a human study. In fact, the authors cite various studies that attempted to correlate telomeres length an longevity in humans but yielded mixed results. Most importantly, these earlier studies had not monitored telomeres length since an early stage in life, something that is critical in order to account for environmental factors that have been shown to accelerate telomere shortening.

In this study, Hedinger et al.

"examined telomere length in red blood cell samples from early in life (at 25 days) and at various points thereafter in a group of zebra finches (n = 99) that were allowed to live out their natural lifespan (ranging from 210 days to 8.7 years). We also examined the effect of reproduction on adult telomere length, by experimentally manipulating whether, and how often, individuals were allowed to breed. These data enabled us to uniquely examine the relationship between telomere dynamics from early in life and total lifespan and reveal that telomere length in early life is a highly significant predictor of the age of death."

While they found no differences between genders, Heidinger et al. did record a decrease in telomere length with age, which was most marked during the first year of life. Interestingly, they also found that telomere shortening was accelerated in birds engaging in reproduction. (When parents say kids make them age faster, they mean it!!) The effect, though, did not persist, and at the next time point the effect of reproduction on telomere length had weaned. Of course, the most interesting result was the significant correlation between telomere length in early life and lifespan. It is important to note that the highly significant correlation was with the measurement taken early in life: length measured at later time points didn't have such a strong predictive effect.

"We found telomere length at 25 days to be a very strong predictor of realized lifespan (P < 0.001); those individuals living longest had relatively long telomeres at all points at which they were measured. Reproduction increased adult telomere loss, but this effect appeared transient and did not influence survival. Our results provide the strongest evidence available of the relationship between telomere length and lifespan and emphasize the importance of understanding factors that determine early life telomere length."

The authors underline what still remains to be seen:

"Whether telomere length change itself plays a directly causative role in determining the pace of decline and age of death is an active area of research. Several mechanistic routes have been identified, mainly from in vitro studies, whereby shortened telomeres can accelerate aging and reduce longevity, primarily involving activation of cellular checkpoints of apoptosis, cell cycle arrest, and impaired stem cell and tissue function."

One thing is certain: any analogous study to be carried in humans should measure telomere length very early in life because, as this study shows, if individuals with shorter lengths die earlier, a sample of lengths measured later in life would already be skewed towards longer length (since individuals with shorter length would have already died) and hence the results would be inconclusive.

[1] Heidinger, B., Blount, J., Boner, W., Griffiths, K., Metcalfe, N., & Monaghan, P. (2012). Telomere length in early life predicts lifespan Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1113306109