“I like the scientific spirit—the holding off, the being sure but not too sure, the willingness to surrender ideas when the evidence is against them: this is ultimately fine—it always keeps the way beyond open—always gives life, thought, affection, the whole man, a chance to try over again after a mistake—after a wrong guess.”
– Walt Whitman
Of all of the techniques used in science, none seem so much like magic as brain mapping. From PET scans to MRIs the process manages to divine not only that thoughts are occurring and where, but how the different parts of the brain communicate with each other, and perhaps, how those parts make up us.
I asked my Human Anatomy and Physiology students to read through some papers in PLOS’s excellent Brain Mapping Methods: Functional MRI section.
Read through the comments to see what they found and which papers they liked!
This concept continues to crop up and in a way it is tied to a concept that continually pops-up in science.
How can an observer tell the difference between dangerous and non-dangerous lab results when they both look the same early on?
As our ability to see into the human body improves with each technological step, we often find ourselves at the fork in the road. We can see that there is clearly a physical change, perhaps a small tumor, or a polyp, or perhaps a constellation of genes, or altered genes. That change could lead to a malignant tumor, a parasite, an amalgam of broken cells, that now wage a single-sided war with their host.
Then again; it might be nothing…
Dennis Normile tackles this in his March 4, 2016 article in Science “Epidemic of Fear”. In fact Sarah Fallon has a great perspective piece in Wired (Wired’s science journalism continues to get better and better).
Normile presents a very nice case for care when evaluating new screening data against past norms. In a case study that follows Fukushima related pediatric thyroid screenings, he presents both the initial driver of fear, in the form of screening results that suggested elevated rates of thyroid nodules in children. Further studies of a “normal” or “unexposed” population describe similar elevated rates of nodule detection in the thyroid, a result that suggests better detection, but not higher risk.
Fallon puts this in perspective, and provides the title of this post, indolent vs. malignant tumors. With each technological leap, we are better able to identify smaller and smaller clusters of cells within the human body. But these advances require further study to provide clues (read as markers) as to whether these clusters of cells will go on to become a malignant monster or perhaps lie dormant for the lifetime of the host. This is in no way an insignificant question. One path takes the patient into the world of invasive treatment, while the second suggests that no further treatment is warranted, while the cluster is small and treatable.
There are many ways forward that were not available to clinicians previously. One of the more promising are gene expression profiles that will be used to classify these early clusters of cells as taking an indolent path over a malignant one. This data has been collected for more than a decade now, and is already being used to assist with these decisions.
Hopefully it will continue so.
In “Epigenetics: A new methyl mark on messengers” Anna M. Kietrys & Eric T. Kool describe a particular methylation step that used to be thought of as damage. This is the latest front in epigenetic changes.
We have studied methylation of histone proteins for some time, and recognizing that this type of modification is a form of regulation. This regulation can modify gene expression in a way that can be passed on to daughter cells and even inherited from one generation to the next.
As the change does not alter the sequence of the genome, but rather the expression properties of genes encoded by the genome, this class of modifications was described as epigenetic. For a deeper history see “A Brief History of Epigenetics” by Gary Felsenfeld from CSHL Press (perhaps not so brief).
The newly described N1-methyladenosine (m1A) methylation may well mark a mRNA for differential expression. The mechanics of this may occur at the level of splicing, wherein these marked pre-mRNAs are spliced more rapidly or efficiently. Speeding them to the cytoplasm quickly and increasing translational accessibility, thus increasing protein levels.
The m1a methylation patterns may also play a part in the regulation, in human and mouse, site preference could be found, while this was less pronounced in yeast. Finally, there is still the problem of which M1A methylations are damage, and which are true signals? The “epitranscriptome” (love the term) may just be coming into focus as a new form of epigenetic regulation.
Let’s say you are interested in researching a gene. Or, maybe, let’s say you are interested in researching a drug.
Or, maybe, just maybe, you want to know about a drug-gene interaction. Where do you find that data?
We have more and more data available to use every minute… which is a good thing. For a researcher, looking through this data the first time (or for the 10th time) the sheer amount of information available can be a little daunting. Initial searches for genes used to yield hundreds of results, and many of those results were incomplete records, or just plan confusing.
Things are improving. Head over to the National Center for Biotechnology Information and search for genes using the keyword “warfarin” and you will get a list of genes back that mention warfarin or have been associated with a record that mentions warfarin. Total hits as of 5 February 2016 was 58, with the top two being VKORC1 and CYP2C9, generally identified as two of the genes encoding products involved in warfarin efficacy.
There are other data sets that to date are even easier to use. Let’s try the same warfarin search on another resource:
But where is all that drug interaction data coming from? PharmGKB provides a more in depth look at all of the gene variants that might influence the function of those genes and the drugs that they are associated with. The same warfain search brings us here, to a wealth of information. I will leave almost all of this data for later, but have a look at the material described in the Pathways segment. Here the role the warfarin plays in the associated gene products functional pathway is graphically displayed. The role that VKORC1 plays is readily apparent, and why warfarins suppression of its function can be seen to play a role in the clotting process.
These are just three sources, covering the same warfarin example. The barriers to this information continue to fall, providing more intuitive access. Perhaps by your second and third searches you will will be more focused on the information you want, rather than wondering how you got there.
In this weeks paper there is a curious statement that comes just towards the end:
The limited availability and cost of pharmacogenetic testing are additional challenges (Tucker, 2008). Most insurance plans will reimburse the cost of pharmacogenetic testing only if it is required by the FDA, medically necessary, or has proven clinical utility (Shin et al., 2009).
There is much excitement surrounding genetic testing and of course in a Gene Technology class we discuss the implications of this sort of approach regularly. If we are looking at pharmacogenomics, or ancestral research the entire process hinges on the sequencing being affordable.
A hidden benefit of the genome project was the development of new technology for sequencing and this is exactly what happened. On a side note, the genome project was started with full knowledge that the current sequencing technology was insufficient for the project and it is this aspect that initially garnered comparisons to the Apollo project. With the completion of the genome project the cost of sequencing has continued to drop as the quality of that same sequencing has increased.
Sometime around 2014 the $1,000 genome race really started to heat up. Nature touched upon the topic here. And then in 2015 Veritas Genetics broke through with their PGP collaboration here.
And with that, the cost barriers seem to be falling, leaving the question of what’s next. Having your genome sequenced comes with allot of challenges, allot of information, both technically and at a deeper level, information with obvious health implications.
Science Isn’t Broken
It’s just a hell of a lot harder than we give it credit for.
Great piece by by Christie Aschwanden with graphics by Ritchie King. Could have done without the expletives (makes it harder to share with younger kids), but other wise love the tone and the interactive examples. I wish that more science writing was done this way; fantastic to have a little widget embedded within the article that helps explain the statistics.
Credit: CDC/ Sally Ezra
There is lots of discussion both in the popular and scientific media about how many people will be infected, and how many more will die. As both the discussion, fear, and grim resolve to do something increase, it is important to understand what uncertainties are in the predictions.
Science Insider has a brief write-up here of the Gomes et al paper in PLoS Currents. The paper is a good read, and pay particular attention to the disease model section to get a nice write-up of the inner workings of their estimates.
The paper does a nice job of breaking down R0, or R nought, the basic reproduction rate. If the paper is to much, run on over to Wikipedia here for a quick brush-up on what R0 is and how it is used.
Christian Althaus’s paper, also in PLoS Currents contains one more piece of the puzzle:
Two key parameters describing the spread of an infection are the basic and the effective reproduction numbers, Ro and Re, which are defined as the number of secondary infections generated by an infected index case in the absence and presence of control interventions. If Re drops below unity, the epidemic eventually stops.
Re is an interesting variable, and this is really the variable that news organizations are struggling to define. Re address the question of what happens to the infection rate if the proper health care steps, “control interventions” are put in place. This gets to the point of the question, how many will continue to be infected?
I had a public speaking teacher in college who used to sit in the back of the classroom and start to moan when the presentations got to boring. If the presentation didn’t improve she would crumple some paper and start to throw it at us, we all knew she was a total nut-job, but the cool thing was that she was always right. When she started to complain, it was only mirroring what the class was already thinking. When she was completely fed-up, we were completely bored. If the internet and the laptop had been invented yet, we would have all wandered away, instead we just stared blankly, hoping it would be over soon.
There are a bunch of things that you can do to engage your audience. Try all of these things, remember, SCIENCE IS TOUGH, GIVE THE AUDIENCE A BREAK!
Reading through the New York Times I came across a cool article describing an unusual relationship between antioxidant type vitamins and health. The NYT article point to the Journal of Physiology article which contains a number of very cool insights. You can take a look at that article here.
The coolest part about all this is how much it makes sense, though at this point, be forewarned, all of this is speculation. During exercise the body needs lots of oxygen, and that is just what the individuals in this study did. Now these individuals were divided into two groups, one taking antioxidant vitamins C and E, the second placebo.
Both groups went through training and both groups showed improvement in running performance. Yet the antioxidant group lacked an increase in “mitochondrial COX4 protein content”. “Big deal”, you say but here is the kicker, and the reason for my little mitochondria picture. COX4 protein content is a proxy for measuring how many new mitochondria are being added to cells. The exercise that the participants are doing should do a number of things to their muscles. Satellite cells should start dividing, muscle mass may increase; skeletal muscles will adapt to the new stresses being placed on them. One of those adaptions are increases in the number of mitochondria within muscle cells.
The authors have a hypothesis that this disruption of mitochondrial biogenesis is intimately tied to the redox state of the cell. If the cells don’t built up enough free radicals, the mitochondrion producing machinery doesn’t get turned on. In the literature this is refered to as the connection between mitochondrial biogenesis and the cellular redox state. That assertion is well supported in the literature; for a quick review of this, have a look here. What is cool about this study is the connection between reasonable oral does of antioxidant vitamins (maybe not reasonable, but have a look here) and endurance training. We will have to see what happens next.
Gillespie Lab 