When I first heard in the media there was a new study of longevity which had produced a model based on your SNP profile that was “77% accurate” as to whether you’d live to the age of 100 or not, I assumed this was confusion or distortion (perhaps The Daily Mail had broken embargo first and its spin was percolating around the mediasphere). But later I listened to one of the researchers on the radio, and though he seemed to want to tone down the certitude as to that prediction, he did not debunk the claim. Whatever the details, I did not believe that the model was that relevant to most people since very few are going to make it deep into their nineties in any case (I did have a grandfather who made it to 100 [in Bangladesh!], so my chance is presumably greater than the norm). The model would be moving you along the margins. Additionally, over the years it has paid off to be skeptical of the discovery of large effect genes for X, Y and Z. When the X, Y and Z has medical significance I’m even more skeptical, because the non-scientific biases within medical research seem to be really strong. There’s a lot of fame and money to be had. Some of the media were asking the researchers up front whether this might unlock the genetic “Fountain of Youth.” This is entrancing stuff.

So is this post from Dr. Daniel MacArthur, Serious flaws revealed in “longevity genes” study, warrants notice:

If the paper’s claims were true they would be truly remarkable. However, the general feeling from the GWAS community is that the identified associations are likely to be largely or even entirely artefactual, the result of failing to fully control for differences in the genotyping methods used in the cases and controls. The study used a mixture of two different genotyping platforms (albeit both made by Illumina) for their centenarians, while the control data was taken from an online database containing samples examined using multiple platforms. Disturbingly, similar potential genotyping bias also affects their replication cohort.

In the Newsweek piece I mentioned yesterday Kári Stefánsson has this to say about one of the platforms:

Kári Stefánsson, the Icelandic geneticist who founded deCode Genetics, knows something about the 610-Quad—his company has used it too. He says it has a strange and relevant quirk regarding two of the strongest variants linked to aging in the BU study, called rs1036819 and rs1455311. For any given gene, a person will have two “alleles,” or forms of DNA. In the vast majority of people, at the rs1036819 and rs1455311 locations in the genome, these pairs of alleles consist of one “minor” form and one “major” form. But the 610-Quad chip tends to see the wrong thing at those particular locations. It always identifies the “minor” form but not the “major” form, says Stefánsson—even if the latter really is present in the DNA, which it usually is. If you use the error-prone chip in more of your case group than your control group—as the BU researchers did—you’re going to see more errors in those cases. And because what you’re searching for is unusual patterns in your cases, you could very well mistake all those errors (i.e., false positives) for a genetic link that doesn’t actually exist.

Stefánsson says he is “convinced that the reported association between exceptional longevity and most of the 33” variants found in the Science study, including all the variants that other scientists hadn’t already found, “is due to genotyping problems.” He has one more piece of evidence. Given what he knows about the 610-Quad, he says he can reverse-engineer the math in the BU study and estimate what fraction of the centenarians were analyzed with that chip. His estimate is about 8 percent. The actual fraction, which wasn’t initially provided in the Science paper, is 10 percent, the BU researchers tell NEWSWEEK. That’s close, given that Stefánsson’s calculations look at just two of the variants found in the study and there may be similar problems with others.

Stefánsson recognizing one of the 150 SNPs as a problematic one is another red flag.  The effect sizes of the SNPs in the study seem really large, so that should make you curious as to what’s going on. Here’s a post from 23andMe suggesting we should be cautious of the results for that reason:

-A large study combining results of four genome-wide association studies of longevity was published in May in the Journals of Gerontology. That study found no associations meeting their pre-specified criteria for genome-wide significance. While they used a more inclusive phenotype (age 90 or older), it is surprising that there could be so many loci associated with survival to age 100 in the new study, some with very large effect sizes, yet none were found in the larger study from earlier this year.

23andMe applied the model (the SNPs) outlined in the paper and attempted to see if it had any utility in to their admittedly small sample within their own database. They found nothing of note:

We took a preliminary look in our customer data to see if the proposed SNP-based model described in Sebastiani et al. is predictive of exceptional longevity. A commonly used measure of test discrimination is to calculate how often, for a randomly selected case and control, a test correctly assigns a higher score to the case. This is known as the “c statistic” or “area under the curve”. The authors of the new study say their model scored a 0.93 for this statistic. But when we compared 134 23andMe customers with age ≥ 95 to more than 50,000 controls, we obtained a test statistic of 0.532, with a 95% confidence interval from 0.485 to 0.579. Using 27 customers with age ≥ 100, we get a value of 0.540, with a 95% confidence interval from 0.434 to 0.645. A random predictor of longevity would give a 0.5 on this scale, so based on our data, performance of this model is not significantly better than random. Even with our small sample size, we can also clearly exclude values as high as the published result of 0.93.

If you go back to Dr. MacArthur’s post he has a chart which indicates that even by eyeballing their are indications that the results in the Science paper were artifacts of the methodological limitations. Newsweek ends with this caution:

Still, one has to wonder how the paper wound up in Science, which, along with Nature, is the top basic-science journal in the world. Most laypeople would never catch a possible technical glitch like this—who reads the methods sections of papers this complicated, much less the supplemental material, where a lot of the clues to this mystery were?—but Science’s reviewers should have. It’s clear that the journal—which hasn’t yet responded to the concerns raised here—was excited to publish the paper, because it held a press conference last week and sent a representative to say as much.

This isn’t about the media. They didn’t have to sensationalize too much; the findings themselves if correct are moderately sensational.  But if Dr. Daniel MacArthur could spot something indicative of serious problems by scanning the supplements presumably it shouldn’t have made it through the review process without the issue being mooted and addressed. But then again, it’s medical genetics, and there’s a lot of pressure to find the roots of human morbidity and mortality. It’s a field where results like ALH 84001 abound. The heart wants what is wants. That’s why it’s nice to focus on less practical evolutionary genetic questions; no one really cares that much whether we’re descended from Neandertals. Right?

Note: And earlier post from Nature with more quotes from scientists who are skeptical of the findings. Also, after reading the posts I did read the original paper. Obviously I was cued to fixate on the particular issues highlighted above, but it is often rather illuminating to contrast the clear and spare summary presented to the public of findings to the numerous moving parts in the guts of the original paper.

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Newsweek has a long piece up which reviews some major issues with the new study of centenarians that’s been all over the media right now. Ed Yong already covered the paper, but I’m going to look at the details myself. Here’s a update from the Newsweek post:

Within an hour of this story’s publication, the Science study’s authors released a statement which a BU spokeswoman described as appearing “because of your inquiry and a similar one from the New York Times concerning methodology used to test 2 of the 150 genetic variants.” Here is what the statement says: “Since the publication of our study in Science, which was extensively peer-reviewed, a question has been raised about two elements of the findings. One has to do with two of the 150 genetic variants included in the prediction model, while the other is related to the criteria used to determine the significance of the individual variants. On the first concern, we have been made aware that there is a technical error in the lab test used on approximately 10% of the centenarian sample that involved the two of the 150 variants. Our preliminary analysis of this issue suggests that the apparent error would not effect the overall accuracy of the model. Because the issue has been raised since the publication of the paper, we are now closely re-examining the analysis. Another question that was raised concerns the criteria used to determine if an association between a genetic variant and exceptional longevity was statistically significant. We used standard criteria for the analysis, and we are confident that the appropriate threshold was used.”

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Of Moose and Men: 50-Year Study Into Moose Arthritis Reveals Link With Early Malnutrition:

“As the study entered its second decade there was increasing evidence of Osteoarthritis (OA) in the moose population,” said lead author Rolf Peterson from Michigan Technological University. “OA is a crippling disease and is identical to that found in humans. It is commonly believed to be caused by ‘wear and tear,’ but the complex causes have remained poorly understood.”
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Over the course of the study the team discovered a rise in OA as the moose population increased, and a decrease when the population fell, leading to the idea that OA is linked to moose malnutrition when food is scarcer. The team found moose that were malnourished when young would develop OA in older age.

“We have shown how malnutrition early in life increased the risk of OA later in life, but this also applies to humans as much as to a herd of moose in the wild,” said Peterson.

“These findings cast new light on how early humans first developed OA,” said co-author Dr Clark Spencer Larsen, an anthropology expert from Ohio University. “The study of human remains from archaeological contexts reveals OA increased where societies changed from foraging plants and animals to an increased dependency on farming.”

Such changes were documented in a mid-continental population of Native Americans 1000 years ago. In this group arthritis increased by 65% as society turned from foraging and hunting to agriculture and the cultivation of maize.

“Initially the increase in OA was put down to increased joint stress due to the labour of agriculture. However research now shows that, like the moose in Isle Royale, nutritional deficiencies early in life may have been the main cause. Early malnutrition was certainly a part of existence for many pre-historic human societies, and remains a fact of life for millions of people across the world, so this study is also relevant for modern human society.”

The original paper is in Ecology Letters, and it should be online at this address. I do wonder if more detailed understanding of the long term impact of early life nutrition is going to drive parents crazy with alarm as every new study which comes out produces a shift in recommendations.

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There will be an interesting presentation tomorrow at the European Society of Human Reproduction & Embryology. Basically the researcher is going to present on a method for predicting when a woman will hit menopause. This part from the press release is the important bit:

“The results from our study could enable us to make a more realistic assessment of women’s reproductive status many years before they reach menopause. For example, if a 20-year-old woman has a concentration of serum AMH of 2.8 ng/ml [nanograms per millilitre], we estimate that she will become menopausal between 35-38 years old. To the best of our knowledge this is the first prediction of age at menopause that has resulted from a population-based cohort study. We believe that our estimates of ages at menopause based on AMH levels are of sufficient validity to guide medical practitioners in their day-to-day practice, so that they can help women with their family planning.”

The method:

By taking blood samples from 266 women, aged 20-49, who had been enrolled in the much larger Tehran Lipid and Glucose Study, Dr Ramezani Tehrani and her colleagues were able to measure the concentrations of a hormone that is produced by cells in women’s ovaries – anti-Mullerian Hormone (AMH). AMH controls the development of follicles in the ovaries, from which oocytes (eggs) develop and it has been suggested that AMH could be used for measuring ovarian function. The researchers took two further blood samples at three yearly intervals, and they also collected information on the women’s socioeconomic background and reproductive history. In addition, the women had physical examinations every three years. The Tehran Lipid and Glucose Study is a prospective study that started in 1998 and is still continuing.

The standard objection to sample size will naturally be brought forth, but if it’s a valid diagnostic I assume it’ll get popular really quickly.

Here are the results:

Dr Ramezani Tehrani was able to use the statistical model to identify AMH levels at different ages that would predict if women were likely to have an early menopause (before the age of 45). She found that, for instance, AMH levels of 4.1 ng/ml or less predicted early menopause in 20-year-olds, AMH levels of 3.3 ng/ml predicted it in 25-year-olds, and AMH levels of 2.4 ng/ml predicted it in 30-year-olds.

In contrast, AMH levels of at least 4.5 ng/ml at the age of 20, 3.8 ngl/ml at 25 and 2.9 ng/ml at 30 all predicted an age at menopause of over 50 years old. The researchers found that the average age at menopause for the women in their study was approximately 52.

Remember this is a presentation at a conference, not a paper. I don’t have much to say about this from a technical perspective. What do I know? But surely this is important from a science-you-can-use perspective.

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From fantasy to fact? Personal Genomics, tipping points and a personal perspective:

But now I think we’ve turned a corner. It feels, to mix metaphors, that we’ve hit a tipping point. The Human genome project, the mapping and sequencing of the/a human genome from 1990 to 2003, cost approximately 2,700,000,000 dollars (that’s 2.7 billion, I wanted to get all the zeros in). Celera did the genome for 300,000,000. The cost of sequencing an entire human genome has been plummeting ever since. In 2007, the cost of sequencing the genome of James Watson (co-discoverer of DNA) was about 2,000,000. The today cost is about 10,000. Complete Genomics and other companies are on the march to quickly reducing the cost of sequencing a genome under 1,000.
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So, within a year, the cost of sequencing your, my, genome will reach 1,000. If not less. We’ve seen this coming for years now, and it’s upon us. But what does it mean? A lot of data. But data means nothing without context and analysis. Sequencing my genome would be a waste of 1,000 dollars if I gleaned nothing from it.

I can believe that we’ll be able to get a tarball with our own full sequence for a reasonable price in a few years. Cheaper than orthodontia and cosmetic surgery even. Though the utility in prevention and treatment is a different matter. Most people already have a treasure trove of data through family history, and that doesn’t seem to change behavior for many in the short-term. Once the magical power of genomics wears off I suspect that knowing you have variant X with risk Y will be less transformative than not.

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Dr. Daniel MacArthur pointed me to this story, Conn. woman alleges genetic discrimination at work:

A Connecticut woman who had a voluntary double mastectomy after genetic testing is alleging her employer eliminated her job after learning she carried a gene implicated in breast cancer.

Pamela Fink, 39, of Fairfield said in discrimination complaints that her bosses at natural gas and electric supplier MXenergy gave her glowing evaluations for years, but targeted, demoted and eventually dismissed her when she told them of the genetic test results.

Her complaints, filed Tuesday with the U.S. Equal Opportunity Commission and Connecticut Commission on Human Rights and Opportunities, are among the first known to be filed nationwide based on the federal Genetic Information Nondiscrimination Act.

What probability do readers put in regards to this being a legitimate complaint? This seems a large firm, so I doubt that group insurance rates would change because of one person (I have heard of this occurring in small businesses where an expensive employee or employee’s family member can effect the rate for everyone else). So if it is legitimate the main issue would have been their fear of future illness, but the woman in question went through a double mastectomy, which I assume would obviate that concern. What am I missing? Are there expectations that she’d be taking medical leave in the future due to follow up operations or treatment?

Update: Brendan Maher has some follow up from Fink’s lawyer.

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With the passage of health care reform, and the shift of the medical profession away from private practice and toward large institutions already, I wanted to revisit some data about the political orientation of medical students and recent graduates surveyed in the mid-aughts. One of the major issues among American elites has been the occupational bifurcation politically between liberals and conservatives, with the former concentrated in the professions which are often affiliated with the managerial state, and the latter within the business sector. Until recently I had assumed that medical doctors were an example of a profession which tended toward conservatism because of the bias toward private practice and the general lack of direct state involvement (as opposed to regulation) in their occupation, but this seems an older model. Political Self-characterization of U.S. Medical Students shows that medical students actually tend toward liberalism vis-a-vis the general population, and even young adults in their primary age group. No doubt this may change as they age, but I am skeptical of this because it looks as if medicine is going to resemble a public sector occupation more, not less, as we proceed. I reformatted table 1, removing a few rows which I felt were extraneous. Additionally, I added columns which show the proportions of medical students by ethnicity and religion (where they received close to 100% response) and the general population ~2008 (from the American Community Survey & Religious Landscape Survey).

There were a few religion categories which don’t seem to map well between what was asked in the survey of medical students and the general population, so I omitted them. Specifically, it seems that many medical students are nominal Christians who simply selected “Other Christian,” while in the general population this class consists mostly of heterodox groups such as Mormons, Jehovah’s Witnesses and Christian scientists. The “Other” religious segment also seems inordinately large, and I suspect that they would be “Unaffiliated” in the Pew survey (if the question is asked so that “Atheist” is part of the category that will scare away a substantial subset of those who aren’t members of organized religions but have some vague supernatural beliefs). Finally, it seems strange to me that they clumped “Native” and “Other” races together in the medical student survey, as it seems likely that many who didn’t want to respond or were mixed-race are in this group, so I didn’t compare it to anything in general population.

No great surprise that pediatricians are more liberal than surgeons. Perhaps I’m employing stereotypes that people may find scurrilous, but I don’t particularly care. Some of the trends among specialties are confounded with the fact that there are differences in sex ratio across them; specialists or those who wish to be specialists are more likely to be male than female, and females are more likely to be liberal than male. Correlations are not necessarily transitive, but I think that’s what you’re seeing here. The liberalism of Asian Americans is not that surprising, but notice that Hindus and Buddhists are even more liberal. The majority of young Asian Americans are now of non-Christian religions, or irreligious, but a significant minority are Christians, and often conservative ones at that. The higher proportion of conservatives among the whole Asian American group is probably a function of the fact that Christians are more comfortable with the conservative movement than non-Christians. If you are a racial minority being a non-Christian makes it very difficult to identify with the modern Republican movement; being a white person at least allows for racial solidarity, while being a conservative Christian allows for ideological solidarity. No matter the “family values” or high incomes of Asian Americans, those who are non-Christian are going to be deeply alienated from the party for reasons of identity for the foreseeable future (yes, I know there are secular libertarian Asian Americans who are Republican. When I was more politically engaged I was in that category).

Interestingly, non-Hispanic whites are represented in proportion to their numbers in the general population among young doctors and medical students, though a bit overrepresented in proportion to their age bracket. As older individuals are more likely to need medical care, and these are more often non-Hispanic white, it will be common for non-white doctors to interact with older patients who grew up at a time when America was an explicitly biracial, and implicitly white, country. I have talked to young Asian American friends who recount experiences with very elderly patients whereby it is difficult for these individuals to grok that they were born and raised in the United States because these patients have an image of America which is derived from their youth.

The prominence of ethnically Asian software engineers, or in scientific institutes, is a well known feature of the American landscape. But these are not occupations which require a great deal of interface with the general American public. Professions like medicine do require that interface, that is one reason that there is focus on getting underrepresented minorities into medicine, so that they can better serve their communities. When it comes to elderly white patients who are going through chronic illnesses at the end of their lives I think it is probably not practical or appropriate to expect too much consciousness raising in regards intercultural dynamics and sensitivity. Rather, I think the onus is going to be on young Asian American doctors to try and understand the perspectives of their patients and the America from which they came, an America which they and their parents have changed in fundamental ways by their very presence.

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Randomized trial of vitamin D supplementation to prevent seasonal influenza A in schoolchildren:

Design: From December 2008 through March 2009, we conducted a randomized, double-blind, placebo-controlled trial comparing vitamin D3 supplements (1200 IU/d) with placebo in schoolchildren. The primary outcome was the incidence of influenza A, diagnosed with influenza antigen testing with a nasopharyngeal swab specimen.

Results: Influenza A occurred in 18 of 167 (10.8%) children in the vitamin D3 group compared with 31 of 167 (18.6%) children in the placebo group [relative risk (RR), 0.58; 95% CI: 0.34, 0.99; P = 0.04]. The reduction in influenza A was more prominent in children who had not been taking other vitamin D supplements (RR: 0.36; 95% CI: 0.17, 0.79; P = 0.006) and who started nursery school after age 3 y (RR: 0.36; 95% CI: 0.17, 0.78; P = 0.005). In children with a previous diagnosis of asthma, asthma attacks as a secondary outcome occurred in 2 children receiving vitamin D3 compared with 12 children receiving placebo (RR: 0.17; 95% CI: 0.04, 0.73; P = 0.006).

I will attest to improvement in my own respiratory health since I began taking vitamin D supplements in 2007, but more studies need to be done to confirm that this is a robust finding.

Citation: Am J Clin Nutr (March 10, 2010). doi:10.3945/ajcn.2009.29094

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I have mentioned before the current fad in vitamin D related papers in the medical literature. It's also broken into the pop culture Zeitgeist as well, I regularly get forwards on the topic. Here is a Google Trends chart for the United States:

The history of medicine is, unfortunately, rather similar to the history of astrology. In fact for much of history doctors are likely to have increased, rather than decreased, mortality, thanks to an ignorance of germ theory and false paradigms such as Humorism. The demand-side pressures for cures & prevention seems to still exert a powerful push toward the rise & fall of fads (see google trends for "low carb" for example). A difference between pre-modern and contemporary fads though is that they're not all capricious today. Unfortunately though medicine is still complex, and the demand-side pressures often require an Answer. You have rafts of correlational studies, with each correlation adding to a positive feedback loop until the fad crests, and a new "it-cure" emerges on the scene (and no surprise that the beer industry is supposedly behind some of the studies which show that drinking in moderation is correlated with greater life expectancy).

All this is why papers like this are important, Vitamin D controls T cell antigen receptor signaling and activation of human T cells:

Phospholipase C (PLC) isozymes are key signaling proteins downstream of many extracellular stimuli. Here we show that naive human T cells had very low expression of PLC-γ1 and that this correlated with low T cell antigen receptor (TCR) responsiveness in naive T cells. However, TCR triggering led to an upregulation of ~75-fold in PLC-γ1 expression, which correlated with greater TCR responsiveness. Induction of PLC-γ1 was dependent on vitamin D and expression of the vitamin D receptor (VDR).Naive T cells did not express VDR, but VDR expression was induced by TCR signaling via the alternative mitogen-activated protein kinase p38 pathway. Thus, initial TCR signaling via p38 leads to successive induction of VDR and PLC-γ1, which are required for subsequent classical TCR signaling and T cell activation.

ScienceDaily has a good summary. This schematic represents the biochemical steps:

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Raising Kids May Lower Blood Pressure:

A new Brigham Young University study found that parenthood is associated with lower blood pressure, particularly so among women.

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The study involved 198 adults who wore portable blood pressure monitors, mostly concealed by their clothes, for 24 hours.
The monitors took measurements at random intervals throughout the day -- even while participants slept. This method provides a better sense of a person's true day-to-day blood pressure. Readings taken in a lab can be inflated by people who get the jitters in clinical settings. It's a real phenomenon known as the "white coat" effect, and it can mess up the results of studies done without the portable monitors.

A statistical analysis allowed the researchers to account for other factors known to influence blood pressure -- things like age, body mass, gender, exercise, employment and smoking -- and zero in on the effect of parenthood. For parents overall, the 24-hour blood pressure readings averaged 116 / 71.

All other things being equal, parents scored 4.5 points lower than non-parents in systolic blood pressure (the top number) and 3 points lower than non-parents in diastolic blood pressure. Holt-Lunstad says the size of the difference is statistically significant, but she warns against hastily making major life changes based on this finding alone.

This finding is interesting because it seems to go against our expectations. I assume that there's no real direct physiological process at work here; e.g., hormone changes due to pregnancy or lactation reducing blood pressure. Rather, it is likely that the choices one makes in life are strongly shaped by having children, and those choices somehow modify health outcomes in ways we don't have a good grasp of yet. The researchers controlled for the variables which they knew about, but there are surely many hidden ones which are the real causes of the effect seen here. Pretty typical correlational study, novel for the against-expectations sign of the value.

Also, I do think it's a little amusing that the work comes out of Brigham Young University. Presumably the authors know a lot about the pro-natalist lifestyle from personal experience. And Mormon "clean living" has resulted in lower morbidity and higher life expectancy from what I have heard.

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