At a Las Vegas gala celebrating Muhammad Ali’s 70th birthday, we premiÃ¨red the video <a href="https://www.23andme.com/pd/" target="_blank" rel="noopener noreferrer">&#8220;Give Us Your Hand,&#8221;</a> featuring the boxing legend and his involvement with 23andMe’s Parkinson’s Disease Research Initiative.
<img loading="lazy" decoding="async" class="alignright size-medium wp-image-11314" title="muhammadhomepagegrab" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/muhammadhomepagegrab-300x184.jpg" alt="" width="300" height="184" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/muhammadhomepagegrab-300x184.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/muhammadhomepagegrab-768x471.jpg 768w, https://blogcms.23andme.com/wp-content/uploads/2012/02/muhammadhomepagegrab-880x540.jpg 880w, https://blogcms.23andme.com/wp-content/uploads/2012/02/muhammadhomepagegrab.jpg 981w" sizes="auto, (max-width: 300px) 100vw, 300px" />
By Emily Drabant
As the Research Manager for the <a href="https://www.23andme.com/pd/" target="_blank" rel="noopener noreferrer">23andMe Parkinson’s Community</a>, I spend my days thinking about ways to advance this research faster, cheaper and more effectively than ever before. We launched this project in 2009 and since that time have been going full steam to make this the largest and most scientifically productive Parkinson’s research cohort in the world. We’ve succeeded on the first goal and already have the world’s largest group of people with Parkinson’s participating in genetics research. And we are making strides towards the second goal with <a href="https://www.23andme.com/about/press/sgk1/" target="_blank" rel="noopener noreferrer">significant scientific discoveries last year</a>.
While our progress is incredible, we have not yet reached our primary milestone of enrolling 10,000 people with Parkinson’s. Our team of scientists believes that having a group of that size will put us in a new era of Parkinson’s research. This will dramatically increase the odds of really understanding the genetics behind the disease. Scientists call this the “statistical power” of research. We call it the power of our research revolution.
<div style="float: right; text-align: justified; width: 300px; background-color: #eee; padding: 15px; margin-left: 10px;">
Meeting ‘The Greatest’ 
By Melissa del Sol
“Let me tell him that you’re ready for him. He just finished eating his chocolate doughnut in the other room.”
Yes. Those were the first words the wife of “The Greatest” used to refer to Muhammad Ali, and they were the perfect first words for her to say. At that point, I was thinking, “Muhammad Ali eats chocolate doughnuts? Yes, he is human! Hmmm&#8230; a chocolate doughnut sounds really good right about now&#8230;”
But I digress.
Rewind to the night before, when Emily, our Parkinson’s Disease Research Manager, and I landed at an airport near Ali’s home. Emily and I had no idea what to expect, but we knew we were excited. One of the world’s most recognized sports figures was about to join our fight against Parkinson’s, and we were about to watch it unfold.
The next morning, five dress changes and two IHOP breakfasts later, we started our drive to Ali’s home. Lonnie, his wife, graciously welcomed us in with an open mind and nothing short of an open heart. We immediately started setting the stage for the magic that was about to happen. It was a perfect morning; the light shone in at just the right angles, the air was filled with hope, and the ease of the set up was quite calming.
And then he appeared&#8230;Muhammad Ali came gliding in using the Ferrari of walkers, with the grace of a well-known fighter and the aura of a legend. Not normally star-struck, I didn’t know what to do. I wanted to shake his hand, give him a hug, and let him know how honored we were to have him on our team, but I could barely get out a “hello.” And just like that, he sat down in the beautiful lighting, and we started to film. I remember that first moment his hand appeared on the film monitor; it was so beautiful, I couldn’t help but start to get a little emotional in that quiet space. I knew our film would focus on his hands, but I really did not anticipate seeing the extent of the power that hands have, to draw you in and share with you a reflection of a life journey.
After filming his hands, we moved on to filming his face and some action shots with Lonnie. Muhammad was quiet, but it was clear that inside he has a vivacious, soulful spirit. Muhammad came to life and even smiled a bit, as his wife shared comical college stories. The charisma in his eyes was just like what I saw in every video and documentary I viewed in preparation of our visit.
What happened in those seven hours, I still can’t eloquently explain, but my hope is that our video will reflect a glimpse of our experiences that day.
As we reached the gates to leave his community, that’s when I lost my composure. I started to cry, not because I was sad or because I felt hopeless, but because I had realized that my experience with the Alis had really hit close to home. Muhammad and Lonnie are a replica of a couple that is very close to my heart. Lonnie cares for Muhammad with every inch of her mind and body. She stands boldly and never allows sadness into her home. Just like the other couple I know, after decades of marriage, they still laugh at each others’ jokes, exchange loving glances, and compassionately hold hands. And just like Muhammad, the man in that other couple has Parkinson’s Disease. Similarly, his eyes are full of life. And just like Muhammad showers his children and grandchildren with love, the love that the man I know has for me, is unparalleled.
My visit with the Alis was not about meeting “The Greatest” or a three-time heavy-weight champion, or any other well-deserved title he has earned throughout the years. It was about meeting a husband, a father, and a grandfather, who just like millions of Americans, looks Parkinson’s in the eye and says, “this is but another fight.” I am so proud to be a part of something so special. I truly believe that there will be “power in numbers” with this fight, and I know that 23andMe’s research will empower those who currently face Parkinson’s Disease and forever have an impact on the disease.
As I came back to the office that Monday morning, everyone wanted to know, “What was he like?,” “What did he say?,” “How did it go?” I couldn’t truly explain the magic that Muhammad, Lonnie, Emily, Elliott (our producer), Rick (our videographer), and I had experienced, as it was a moment in time, a memory that could not be re-created. But at the core, it was simple: Muhammad Ali is a gracious man, a human being just like you and me, who happens to be a man of great vision, a man who has changed lives, and a man who will continue to change lives for years to come.
</div>
As enrollment slowed around 6,000 people, I began to brainstorm on ways to get more people with Parkinson’s involved. We’ve worked directly with many patient advocacy groups to spread the word – especially with the <a href="http://www.michaeljfox.org/" target="_blank" rel="noopener noreferrer">Michael J. Fox Foundation</a>, the <a href="http://www.parkinson.org/" target="_blank" rel="noopener noreferrer">National Parkinson Foundation</a>, and <a href="http://www.thepi.org/" target="_blank" rel="noopener noreferrer">The Parkinson’s Institute</a>. But I wondered: how could we reach people who aren’t linked up with an advocacy group or a support group, and perhaps aren’t even very public about the fact that they have Parkinson’s? I began to think that if we did something really big – if we made a splash in a really public way – that it would truly raise awareness about this research and give people who want to participate the chance to do so. I hear from people with Parkinson’s all the time saying ‘I had no idea this was available. I didn’t know I could advance research from home”.
In considering ways to make this research public in a really big way, we naturally started to think about working with a celebrity with Parkinson’s. At the top of that list is Muhammad Ali, one of the world’s most recognized athletes, who has been fighting Parkinson’s for 25 years. We spoke to one of our collaborators, Dr. Bill Langston, and he suggested we contact Muhammad’s wife, Lonnie. “When Lonnie says something is going to happen, she will make it happen,” he said.
Those words were completely true. In December, my colleague, Melissa Del Sol, and I flew to Arizona to film Muhammad and interview Lonnie at their home. It was a magical experience and you can read more in Melissa’s blog.
I didn’t plan to conduct the interview – the director of the video was going to handle that – but at the last minute he decided it made more sense for me to do it. I did it off the cuff and asked questions that I wanted to know as a scientist, as someone with personal connections to Parkinson’s, and as an admirer of Muhammad Ali.
We talked about Muhammad’s diagnosis of Parkinson’s. When he first started showing symptoms they were quite minor – a tremor in his finger. The doctor said it was Parkinson’s syndrome, which meant that it would never progress into full blown Parkinson’s, but rather was just a Parkinson’s-like symptom. But over time his symptoms did progress. When they went to a Parkinson’s specialist he confirmed that it was in fact Parkinson’s disease. I asked Lonnie how they both reacted to this.
“Muhammad deals with adversity a lot different than most people. To him, I don’t think it really registered, because he was still doing a lot of what he wanted to do,” she said. “He’s always had that thing about mind over matter … where he thought he could overcome this on his own. It took a real long time for him to realize that it wasn’t going to work that way.”
<img loading="lazy" decoding="async" class="alignright size-medium wp-image-11327" title="Emily&amp;Melissa" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-300x257.jpg" alt="" width="300" height="257" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-300x257.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-768x659.jpg 768w, https://blogcms.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-1024x878.jpg 1024w, https://blogcms.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-880x755.jpg 880w, https://blogcms.23andme.com/wp-content/uploads/2012/02/EmilyMelissa-1180x1012.jpg 1180w" sizes="auto, (max-width: 300px) 100vw, 300px" />
“However for me it was a little bit different because when you say disease it is a lot different than hearing syndrome. Any “disease” sounds very fatalistic. So I had to do a bit of investigating.”
As Lonnie learned more, she and Muhammad started to get involved in research. When he realized that he could advocate for others with Parkinson’s, he decided to go public with his diagnosis. Muhammad and Lonnie founded the Muhammad Ali Parkinson’s Center in Arizona in 1997 and have made tremendous contributions to research.
“Muhammad and I have sort of grown up with the research,” Lonnie said. “A lot of research has been done to advance our understanding of what this disease is and where it comes from and some of the factors that may contribute to it. So we are very hopeful about the research. But when we first started out it was funny because we were told that in ten years we would have a cure and it’s just a function of money. Well now we know that’s not true. Ten years have come and gone and there has been a lot of money, but it’s a lot more complex than that. … We are really hopeful that this is one of the neurological diseases that will be given a cure.”
This point is not lost on us at 23andMe. Indeed, the slow pace of research into Parkinson’s and many other diseases was what motivated us to launch our online research platform for all in the first place. We wanted to speed up research and do it bigger than ever before. We knew we needed to change the research model if we were going to make progress in the same lifetime as those who are currently battling Parkinson’s.
“I think 23andMe is cutting edge technology that has been introduced to address this illness and to look at it in a different lens; getting to the genetic basis of what causes this illness, why do some people get it and why is it that some people don’t. The sooner we understand that,” said Lonnie, “the sooner we will be able to address treatment – better treatment – options for people.”
She continued, “Looking at the genetics of the illness and the way 23andMe is doing it &#8211; getting a broad base of people to participate in the research &#8211; is extremely important to finding a cure. Then all the added things 23andMe does with regards to the person &#8211; giving them information about their personal health history and how to keep them healthy aside from Parkinson’s, because what people forget is that people with Parkinson’s don’t just have Parkinson’s, they have a lot of other illnesses. They may have hypertension, they may have diabetes. They could have a lot of other things which agitate the Parkinson’s that they have to live with. So getting all that information back about what works best for you on an individual basis … is very important. It’s a wonderful thing that 23andMe has done, trying to partner with other researchers around the country to try to answer some of these complex questions.”
I left Arizona feeling inspired, full of gratitude and hope for the future of Parkinson’s research. When I was a neuroscientist at Stanford doing brain imaging research I never could have imagined that one day I would be working with Muhammad Ali on a video project. But there is no doubt in my mind that this video, and Muhammad and Lonnie’s involvement with 23andMe, will push 23andMe’s Parkinson’s research to new heights. Parkinson’s disease can be devastating for those with the illness, but sometimes we forget that such a daunting diagnosis can also inspire great courage.
In this job working with the Parkinson’s community, I am continually awed by the reservoir of spirit found among those facing the disease. Just as Muhammad Ali inspired and continues to inspire generations of people with his courage and spirit, those with Parkinson’s who are bound together to fight this disease can inspire us all.
Learn more and see the video at <a href="https://www.23andme.com/pd" target="_blank" rel="noopener noreferrer">www.23andme.com/pd</a>

23andMe Blog

23andMe Blog Team

23andAli

<img loading="lazy" decoding="async" class="alignright wp-image-10993 size-medium" style="border: 1px solid #ccc;" title="sebastiani_longevity_screenshot" src="http://35.88.189.111/wp-content/uploads/2012/01/sebastiani_longevity_screenshot-294x300.png" alt="" width="294" height="300" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/01/sebastiani_longevity_screenshot-294x300.png 294w, https://blogcms.23andme.com/wp-content/uploads/2012/01/sebastiani_longevity_screenshot.png 700w" sizes="auto, (max-width: 294px) 100vw, 294px" />
By David Hinds, Chuong Do, and Shirley Wu
In January we wrote about <a href="https://blog.23andme.com/articles/seeking-the-secrets-of-the-super-long-lived" target="_blank" rel="noopener noreferrer">the challenging search for genetic influences on human longevity</a>, touching on two of the most recent studies as examples of how elusive solid findings have been. Because one of these studies was a new version of a paper that was previously retracted, we took a particular interest to see if the concerns raised by the previous analysis were addressed. What follows is a technical review of “<a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848" target="_blank" rel="noopener noreferrer">Genetic Signatures of Extreme Longevity in Humans</a>”, published last month in PLoS ONE.
Although Paola Sebastiani and Thomas Perls (the main authors on both papers) do not directly discuss their previous study, their new version does appear to resolve many of the issues from the prior manuscript, and their GWAS results are substantially improved. They now report just one SNP clearly associated with longevity, rs2075650 near APOE. They also present a revised genetic model for predicting longevity based on 281 SNPs representing the common genetic variants most significantly associated with longevity in an analysis of 801 centenarians and 914 healthy control individuals.
As described in the paper, the performance of the model remains quite impressive:
<ul>
<li>89% sensitivity and 89% specificity (“area under the curve”=AUC=0.95) on the discovery set,</li>
<li>60% sensitivity and 58% specificity (AUC=0.58) on a replication set of 253 independent cases and 341 genetically-matched controls, and</li>
<li>78% sensitivity and 61% specificity (AUC=0.74) on a replication set of 60 independent cases and 2,863 unmatched controls.</li>
</ul>
We wanted to understand the meaning of these results and to determine whether this model could be used to predict longevity for 23andMe customers. To this end, we examined a few specific aspects of the study in closer detail.
<h6>
 
1. Performance on discovery data.</h6>
Our first area of interest was in understanding the authors’ proposed methodology for constructing the predictive models. In the paper, the authors describe a procedure for constructing an ensemble of nested predictive models, using SNPs that were identified as the top associations in a GWAS. To choose between different models, the authors described a procedure that involved repeatedly splitting the discovery set into training and testing folds; however, in each case, the set of SNPs that were candidates for inclusion were taken from the top hits in the GWAS of the entire discovery set. We were concerned that constructing models in this way could lead to extremely biased estimates of accuracy since the candidate SNP selection process uses information from the testing folds.
To evaluate this, we simulated genome-wide association studies of 801 cases and 914 controls across 200,000 independent SNPs, one representing the true association with rs2075650, and the other 199,999 not associated with longevity (reduced from the 243,980 SNPs in the paper to account for potential non-independence in the original set). In each simulation, we selected the 281 most strongly associated SNPs and built nested prediction models as described in the longevity study. Across 1,000 simulated datasets, when we evaluated the resulting models by 10-fold cross validation, we observed an average sensitivity of 88%, an average specificity of 89%, and an average AUC of 0.95, very close to the reported values. Thus, the reported performance in the discovery data seems consistent with the null hypothesis that rs2075650 is the only informative SNP in the model, and the performance difference between a 281-SNP model and a 1-SNP model could be entirely explained by overfitting.
<div style="border: 1px solid #ccc; margin-bottom: 15px; margin-top: 10px; padding: 10px; text-align: center;"><img loading="lazy" decoding="async" class="aligncenter wp-image-11276" title="sim_plot" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/sim_plot.png" alt="" width="576" height="288" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/sim_plot.png 800w, https://blogcms.23andme.com/wp-content/uploads/2012/02/sim_plot-300x150.png 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/sim_plot-768x384.png 768w" sizes="auto, (max-width: 576px) 100vw, 576px" />Performance of risk model ensembles from Sebastiani et al. 2012, trained on simulated random data containing only one true association. The left plot shows 10-fold cross-validation performance when SNPs are pre-selected using the entire discovery sample. The right plot shows 10-fold cross-validation performance when no SNPs are pre-selected. Shaded regions denote 95% confidence bands. Note the similarity of the sensitivity and specificity curves in the left plot with Figures <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848#pone-0029848-g004" target="_blank" rel="noopener noreferrer">4B</a> and <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848#pone.0029848.s004" target="_blank" rel="noopener noreferrer">S4A</a> from the paper, which the authors use to justify including 281 SNPs in their model. In contrast, in the right plot, model accuracy (in terms of AUC) decreases with increasing model size.</div>
Although the authors do acknowledge the possibility of overfitting, we suspect that some readers may be surprised at the extent to which “pre-selecting” candidate SNPs for a model (based on the results of a genome-wide scan where the validation set has not been excluded) can lead to highly inflated estimates of accuracy, even when the underlying data is essentially random. In particular, these results cast doubt on the validity of the resampling experiments used by the authors to justify their choice of model size since the predictive accuracies estimated by the authors’ bootstrapping procedure are just as vulnerable to overfitting the discovery data as the cross-validation protocol in our simulation above.
Had SNP selection been performed in the “inner loop” of the validation (i.e., only using the training portion of each train/test split), then the estimates of performance for different models would not have suffered from the bias shown here and substantial overfitting could have been avoided. In the simulations above, if one uses a correct cross-validation procedure, model accuracy decreases with model size, consistent with the fact that there is just one true association in the data.
<h6>2. Population stratification in 23andMe data.</h6>
Of course, even a model that is overfit may have some amount of predictive power as long as the “noisy” predictions from the model show some meaningful correlation with true phenotypes. Our second step was to implement the 281-SNP model described in <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848#pone.0029848.s022" target="_blank" rel="noopener noreferrer">Table S1</a> of the paper and test it in a collection of over 80,000 23andMe research participants with predominantly European ancestry.
In preparation for assessing the performance of the model, we examined whether there was any evidence that the risks predicted by the model varied with ancestry in the 23andMe data. We used <a href="https://en.wikipedia.org/wiki/Principal_component_analysis" target="_blank" rel="noopener noreferrer">principal components analysis</a> to extract the two most important dimensions of ancestry in these individuals, and plotted the proportion of individuals with predicted probability of exceptional longevity (according to the model) &gt; 0.5 for 23andMe participants on these dimensions. Because living to age 100 is so rare, this plot effectively shows the false positive rate of the classifier, or “1-specificity”, in 23andMe participants, assuming a prior probability of exceptional longevity of 0.5 to be consistent with results in the paper.
<div style="float: right; text-align: right; border: 1px solid #ccc; padding: 10px; margin-left: 15px; width: 338px;"><img loading="lazy" decoding="async" class="alignright wp-image-10994" title="map1" src="https://blog-api.23andme.com/wp-content/uploads/2012/01/map1.png" alt="" width="338" height="338" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/01/map1.png 480w, https://blogcms.23andme.com/wp-content/uploads/2012/01/map1-150x150.png 150w, https://blogcms.23andme.com/wp-content/uploads/2012/01/map1-300x300.png 300w, https://blogcms.23andme.com/wp-content/uploads/2012/01/map1-271x271.png 271w, https://blogcms.23andme.com/wp-content/uploads/2012/01/map1-372x372.png 372w" sizes="auto, (max-width: 338px) 100vw, 338px" />Proportion of individuals in 23andMe database with predicted longevity probability &gt; 0.5 based on Sebastiani&#8217;s model. (LB=Lebanon, IR=Iran, IT=Italy, GR=Greece, ES=Spain, FR=France, BE=Belgium, UK=United Kingdom, RO=Romania, HU=Hungary, AT=Austria, DE=Denmark, NO=Norway, SE=Sweden, CZ=Czech Republic, UA=Ukraine, PL=Poland, FI=Finland, LT=Lithuania).</div>
In the figure to the right, we show results for areas of the plot with at least 50 participants. The labels indicate country of origin for participants with four grandparents from the same country, or &#8216;AJ&#8217; for self-identified Ashkenazi Jews. We see a trend in risk scores, with lower probabilities of longevity assigned to Ashkenazi Jews, Southern, and Eastern Europeans compared to Western and Northern Europeans. Specificity of the model varies from &gt;70% for Ashkenazi Jews to &lt;50% for Scandinavians.
The plot provides evidence that the overall risk scores predicted by the model correlate with ancestry in the 23andMe population. Although this observation might seem surprising, given that the risk model was trained on cases and controls that were matched for genetic ancestry, there is no contradiction here &#8212; it is plausible that the genetic component of exceptional longevity might vary systematically with ancestry. Furthermore, it is certainly true that individual alleles in the risk model are in some cases correlated with ancestry; for instance, rs2075650 near APOE shows a gradient in minor allele frequency from south to north across Europe.
The fact that the risk score from the model stratifies by ancestry suggests that the latter should be taken into account as a potential confounding factor when measuring performance, especially when comparing performance in datasets with differing composition by ancestry. This result might complicate interpretation of the authors&#8217; second replication experiment, because that experiment used cases and controls that were not matched for ancestry. (In the paper, the authors did look for such an effect, but <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848#pone.0029848.s010" target="_blank" rel="noopener noreferrer">Fig. S10</a> does not provide strong evidence for the absence of residual population stratification.)
<h6>3. Performance on 23andMe data.</h6>
From the 23andMe research database we selected a cohort of unrelated individuals of primarily European ancestry, including 31,547 participants with current age &lt; 50, and 2,506 participants with age &gt;= 80. Using logistic regression, we tested whether there was an association between longevity (age &gt;= 80) and the predicted longevity score (converted to log-odds), adjusting for gender. Interestingly, despite the model overfitting described earlier, we found a weak but significant association between the two (P=0.021, odds ratio (OR) = 1.03).
However, we saw a stronger association between longevity and the single APOE SNP rs2075650 (P=2.8e-5, OR=0.83); this association was the only statistically genome-wide significant association in the authors’ analysis as well. We also saw a strong association between longevity and the first five principal components of ancestry (P= 100), the association with rs2075650 was no longer significant but had a larger effect size in the expected direction (P=0.075, OR=0.44). The longevity risk score was still not associated with age (P=0.97) after controlling for ancestry and the APOE SNP, a result which is not particularly sensitive to the age cutoff used (P=0.30 using 479 individuals with age &gt;= 90, or P=0.28 using 141 individuals with age &gt;= 95).
<div style="float: right; text-align: right; border: 1px solid #ccc; padding: 10px; margin-left: 15px; width: 338px;"><img loading="lazy" decoding="async" class="alignright wp-image-11277" title="age" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/age.png" alt="" width="338" height="338" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/age.png 480w, https://blogcms.23andme.com/wp-content/uploads/2012/02/age-150x150.png 150w, https://blogcms.23andme.com/wp-content/uploads/2012/02/age-300x300.png 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/age-271x271.png 271w, https://blogcms.23andme.com/wp-content/uploads/2012/02/age-372x372.png 372w" sizes="auto, (max-width: 338px) 100vw, 338px" />Median age of 23andMe research participants by self-identified (AJ) or 4-grandparent-determined ancestry.</div>
There are multiple reasons why the risk score might not replicate in the 23andMe cohort. For example, our younger longevity phenotypes are less extreme than the phenotypes in the PLoS ONE study, and our small group of centenarians has lower power for detecting small effects on risk. In addition, our self-reported age data may be less reliable for extreme ages, though to reduce the risk of errors from incorrect age reporting, the above analyses were conservatively restricted to individuals who provided their date-of-birth in at least two separate forms or surveys on the 23andMe website and excluded those who reported conflicting birth years in any of these locations.
Interestingly, in our cohort, Ashkenazi Jewish ancestry is positively associated with longevity (for age &gt;= 80: P=3.4e-4, OR=2.2), while in the PLoS ONE study, Ashkenazi Jewish ancestry seems to be negatively associated with longevity. This almost certainly reflects a difference in how individuals were selected for the two studies, rather than a difference in genetic predispositions. If we exclude Ashkenazi Jews from our regression analysis, the longevity score is slightly more predictive on its own (P=0.019, OR=1.03), but the association again goes away once we add the top five principal components and APOE to the model (P=0.22, OR=1.02).
<h6>Concluding thoughts</h6>
The genetic model presented by Sebastiani and Perls appears to be overfit to their training data, and we further see very little correlation between the predictive scores generated from their model and longevity in the 23andMe research cohort, once the effects of ancestry and the significant APOE association are taken into account. Even without these additional corrections, the ability of the authors’ risk score to distinguish long-lived individuals in our database is poor.
It is worth noting that a model based on only the single APOE association in the paper achieves an AUC of 0.58 (0.52-0.63) among individuals with age &gt;= 100 in the 23andMe cohort, consistent with the authors’ estimate of 0.62; the effect weakens with decreasing age cutoff (e.g., AUC=0.53 (0.49-0.56) for age &gt;= 95). When combined with the 280 other SNPs in the authors’ model, however, the performance in our cohort drops to AUC=0.49 (0.39-0.60) among centenarians (or AUC=0.52 (0.47-0.56) for age &gt;= 95), which is statistically indistinguishable from random guessing. While the ability of our cohort to detect meaningful association may be limited due to sample size, our confidence intervals are at least sufficiently narrow to exclude the point estimate of AUC=0.74 reported by the authors for their second replication study.
We remain concerned that despite clear improvements in the authors’ revised study, the analysis may nonetheless be susceptible to subtle biases, due to the way in which cases and controls were selected. Because of the numerous potential confounding factors related to the separate ascertainment of cases and controls and the fact that most of the controls were derived from a single source, it may be impossible to formally show that all sources of bias have been adequately controlled in the authors’ analyses.
An alternative analysis that at least partially addresses some of the concerns above (without genotyping additional samples) would be to repeat the discovery analysis using a random subset of NECS cases and Illumina controls (using a properly cross-validated model selection procedure), and reserving the remainder of the NECS cases and controls for replication. This would not resolve the potential for confounding in the model building step, but would at least reduce the potential for bias in the replication set. A more convincing demonstration would require constructing and evaluating the model using a dataset where such confounding factors are simply <a href="http://blog.goldenhelix.com/?p=322" target="_blank" rel="noopener noreferrer">absent by design</a> (i.e., where cases and controls are drawn from a single underlying population and genotyped together); this would certainly involve genotyping of more controls than in the study, but unlike centenarians, controls are relatively easy to come by (we have lots!).
In our view a predictive genetic model for longevity remains elusive but we are optimistic that continuing efforts like the <a href="http://www.bumc.bu.edu/centenarian/" target="_blank" rel="noopener noreferrer">New England Centenarian and Supercentenarian Studies</a> will keep adding to our knowledge of this most human of traits.

Studies of Extreme Longevity Extremely Challenging

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Sickle Cell Celebrities
<img decoding="async" class="alignnone wp-image-11141" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-300x300.jpg" alt="" width="300" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-300x300.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-150x150.jpg 150w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-271x271.jpg 271w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-372x372.jpg 372w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo-574x574.jpg 574w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Miles_Davis_by_Palumbo.jpg 600w" sizes="(max-width: 300px) 100vw, 300px" />
A number of famous individuals have suffered from sickle cell anemia including Miles Davis, perhaps the most famous jazz musician to have lived (some consider his platinum-selling album Kind of Blue to be THE jazz album), and Tionne &#8216;T-Boz&#8217; Watkins, a singer and founder of the R&amp;B/hip-hop group TLC. NFL superstar Tiki Barber also has sickle cell anemia and has launched a health education campaign, Be Sickle Smart: Ask Tiki about Iron. Although there is no cure for sickle cell anemia, blood transfusions can be used to treat severe anemia.
Photo by Tom Palumbo from New York City, USA (Miles Davis) [<a href="http://www.creativecommons.org/licenses/by-sa/2.0/" target="_blank" rel="noopener noreferrer">CC-BY-SA-2.0</a>], via Wikimedia Commons.
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<a href="http://www.23andme.com/topics/carrier/sickle-cell-anemia/">Sickle cell disease</a> – a group of inherited red blood cell disorders – affects millions of people around the world, but is particularly common among those with ancestry tracing to sub-Saharan Africa. In the United States alone, about 100,000 people have the disease and roughly<a href="https://www.cdc.gov/ncbddd/sicklecell/data.html" target="_blank" rel="noopener noreferrer"> one in 500</a> black or African-American babies is born with it.
Sickle cell disease is caused by having two mutated copies of the hemoglobin (HBB) gene (one from mom and another from dad). A person with two copies of the S version of the HBB gene (S is short for “sickle”) typically has sickle cell anemia; other versions of HBB are associated with<a href="https://www.cdc.gov/ncbddd/sicklecell/facts.html" target="_blank" rel="noopener noreferrer"> milder forms of anemia</a>. The rates of sickle cell disease are so high because roughly<a href="https://www.cdc.gov/ncbddd/sicklecell/data.html"> one in 13</a> Americans with African ancestry carries one mutated copy of the HBB gene and thus has <a href="https://www.cdc.gov/ncbddd/sicklecell/traits.html" target="_blank" rel="noopener noreferrer">sickle cell trait</a>. People with sickle cell trait typically do not have any symptoms of sickle cell disease, but can pass the disease on to their children – if both parents are carriers (and thus have the trait) there is a 25% chance that their child will develop sickle cell disease, a 50% chance that their child will also be a carrier, and only a 25% chance that their child will not be affected or a carrier. For people planning to have a child, knowing one’s carrier status could be useful information.
The mutation underlying sickle cell disease causes red blood cells, which are responsible for delivering oxygen to the tissues, to stiffen and take on a crescent shape that clogs blood vessels. As a result, people with sickle cell anemia have a hard time getting oxygen to certain parts of the body. In the short term, this causes excruciating episodes of pain called &#8220;crises” and in the long term repeated episodes of reduced blood flow can damage organs.
Why would a genetic mutation that causes a harmful disease to survive through evolution to the high frequency with which we observe it today? It turns out that people with the S version of the HBB gene are protected against malaria and thus survive better in parts of the world where malaria is common. Over time, having just one S version of HBB – and thus having the <a href="https://www.cdc.gov/ncbddd/sicklecell/traits.html" target="_blank" rel="noopener noreferrer">sickle cell trait</a> – improved the survival rate in human history so much that this mutation continues to exist in spite of the disease burden it causes. Read more about evolutionary trade-offs in genetics in a <a href="../2008/07/22/the-ultimate-trade-off-genes-environment-and-why-we-crave-twinkies/" target="_blank" rel="noopener noreferrer">previous blog post</a>.
<img loading="lazy" decoding="async" class="alignnone size-full wp-image-11179" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/Sicklecells.jpg" alt="" width="250" height="200" />Sickle cell anemia causes red blood cells, normally flexible and disc-shaped, to form stiff crescents that can clog blood vessels. (Image via Wikimedia Commons.)
<img loading="lazy" decoding="async" class="alignright wp-image-11174 size-medium" src="http://35.88.189.111/wp-content/uploads/2012/02/Malaria_geographic_distribution_2003-300x135.png" alt="" width="300" height="135" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/Malaria_geographic_distribution_2003-300x135.png 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/Malaria_geographic_distribution_2003.png 600w" sizes="auto, (max-width: 300px) 100vw, 300px" />The geographic distribution of the sickle cell trait and malaria are strikingly similar. This map shows that malaria is found worldwide in tropical and subtropical regions (shaded yellow). (Image via Wikimedia Commons.)
February is <a href="http://www.history.com/topics/black-history-month" target="_blank" rel="noopener noreferrer">Black History Month</a> – stay tuned for more posts!

One in Thirteen African Americans has a Sickle Cell Trait

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Your doctor undoubtedly knows quite a lot. She went through four grueling years of medical school, passed a rigorous set of board exams, and completed at least one intensive residency in her specialty.
What may surprise you, however, is that she may not know much about pharmacogenetics, the study of how genetic variation affects drug response. Fortunately, she may recognize that this new field is quickly becoming an important part of medicine.
<h2>Perceptions of Pharmacogenetics</h2>
Felix Frueh, vice president of Medco Health Solutions and recently featured on our <a href="../articles/a-prescription-for-personalizing-medicine/">blog</a>, joined other scientists to survey physicians across the United States on their perceptions and use of pharmacogenetic testing.
This survey, the first large-scale assessment of pharmacogenetic attitudes and practices in the medical community, aimed to reach physicians across various ages, geographic locations, training backgrounds, and specialties.  They sent nearly 400,000 surveys, and approximately 3% were returned. After analyzing these thousands of responses, Frueh and his coworkers <a href="https://www.ncbi.nlm.nih.gov/pubmed/22278335" target="_" rel="noopener noreferrer">published</a> their findings in Clinical Pharmacology and Therapeutics last week.
<h2>A Knowledge Gap</h2>
The survey-based study simultaneously revealed an interest in and a lack of pharmacogenetics knowledge.
Almost every doctor who responded (97.6%) believed that genetic variation may influence drug response. This, however, stood in contrast to the small fraction of physicians (10.3%) who felt they had been adequately trained in pharmacogenetics. Fewer than one in three doctors had received formal field training.
According to the survey, most doctors primarily get their information about genetic testing from coworkers, drug labels and the Internet.  Not surprisingly, these doctors, many of whom felt under-trained and/or uncertain about the validity of the currently reported associations, did not use genetic testing very often.
Only about 13% said that they had ordered a genetic test for a patient in the last months; surprisingly, twice this number expect to order one in the next six months.  This projected increase in test orders may indicate a growing appreciation for the potential benefit of pharmacogenetic testing.
<h2>An Opportunity</h2>
Although the survey results indicate that most doctors do not regularly use genetic testing, the study did provide insights into which ones do.
As one might expect, doctors who received training in pharmacogenetics were about 1.6 times more likely to be early adopters of genetic testing. In addition, oncologists and surgeons (doctors in fields where pharmacogenetic testing is better established) were more likely to use genetic testing than general or family practitioners.  Furthermore, doctors in private practices were more likely to be early adopters than those working in a hospital or HMO.  A
ge and gender were not significantly associated with being an early adopter. However, physicians who had graduated from medical school 15-29 years ago were more likely to be early adopters than those who graduated more than 30 years ago.
<h2>Reimbursement Question</h2>
The growing popularity of genetic testing among physicians raises the question of who will pay for these new diagnostics. The doctors’ almost unanimous answer to this quandary was the health insurers. About a third of the responders felt that insurers- private, state, or federal- should provide full coverage for pharmacogenetic testing. Close to two-thirds felt insurers should provide full coverage in some situations. Indeed, approximately 9% of the doctors cited lack of insurance coverage for one of the primary reasons for not ordering tests.
Dr. Frueh and his coworkers acknowledge a potential bias in their study: the doctors most familiar with pharmacogenomics testing are also the doctors most likely to respond to a volunteer survey about pharmacogenomics.
The researchers, therefore, suggest that the actual percentages of doctors who received formal pharmacogenomic training and who regularly use genetic testing may be even lower than that predicted from the surveys.    Their conclusions from this study, especially in light of this potential bias, underscore the need for better pharmacogenetic education in the medical community.

What Does Your Doctor Know About Genetic Testing For Drug Response?

<img loading="lazy" decoding="async" class="alignnone size-medium wp-image-11065" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/iStock_000014838144XSmall-300x199.jpg" alt="" width="300" height="199" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/iStock_000014838144XSmall-300x199.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/iStock_000014838144XSmall.jpg 425w" sizes="auto, (max-width: 300px) 100vw, 300px" />
Many couples who would like to start a family have difficulty doing so.
This disappointing and frustrating situation is more common than many people realize, affecting approximately one couple out of six worldwide.
Given that female infertility issues receive so much attention, it may surprise some to learn that a couple’s inability to conceive is attributable to male infertility approximately half of the time.
<h6>Most Common Reason for Male Infertility</h6>
One of the most common reasons for male infertility is azoospermia, a condition of having no sperm in the semen. Azoospermia is present in about 20% of male infertility cases in Europeans and 25% of male infertility cases in Chinese men.  There are two main types of azoospermia: obstructive azoospermia and non-obstructive azoospermia (NOA).
In obstructive azoospermia, the sperm are blocked by a physical obstruction, such as a vasectomy.  In NOA, no physical barrier to sperm delivery is present and the absence of sperm in the semen is usually due to a lack of sperm production.

<h6>Genetic Research</h6>
Recently, a group of researchers from China, led by Zhibin Hu and Jiahua Sha of Nanjing Medical University, <a href="https://www.ncbi.nlm.nih.gov/pubmed/22197933">reported novel genetic associations</a> with NOA in the journal Nature Genetics.
These researchers compared about 3,000 Chinese men diagnosed with NOA to 5,734 Chinese men without the condition. They found two variants associated with higher odds of NOA.  They also found a third SNP associated with NOA, although the effect was slightly smaller impact.
<h6>GENES Involved</h6>
The first of these SNPs is located near the PRMT6 gene.  Some studies suggest that a gene called PRMT5, which is related to PRMT6, may be involved in sperm and egg development in fruit flies, mice, and possibly some fish.
In humans, the enzyme encoded by PRMT6 may regulate another gene thought to be involved in pairing together chromosomes during the formation of sperm.  The second SNP, , is located near the genes PEX10 and MMEL1, both of which have also been associated with male fertility in other animals.
The question of why some couples struggle to conceive is of great personal importance and impact to many, and genetic research is just starting to uncover common genetic variation that may influence human fertility.
Many genes and non-genetic factors are likely to be involved in NOA, and many other conditions may contribute to male infertility besides NOA. This study provides insights into some possible genetic factors influencing male infertility in Asian men but more studies are needed to confirm these associations &#8212; and find new ones &#8212; in other populations.

Genetic Variants Linked to Male Infertility in Asians

<img loading="lazy" decoding="async" class="alignright wp-image-2176 size-full" src="http://35.88.189.111/wp-content/uploads/2008/12/cholesterol.jpg" alt="" width="350" height="233" srcset="https://blogcms.23andme.com/wp-content/uploads/2008/12/cholesterol.jpg 350w, https://blogcms.23andme.com/wp-content/uploads/2008/12/cholesterol-300x200.jpg 300w" sizes="auto, (max-width: 350px) 100vw, 350px" />
By Bethann Hromatka, Ph.D. 

HLDL is the “bad” cholesterol that clogs arteries and is linked to coronary heart disease. Although people can do a lot to lower LDL levels and prevent heart disease – eating healthy, exercising, and taking certain medications – it’s also likely that genetics influences the relationship between LDL and heart disease.
For instance, some studies suggest that a particular version of the KIF6 gene called 719Arg may be linked to both heart disease and response to statins, a class of drugs used to lower LDL. The involvement of this SNP in the complex interplay between LDL cholesterol and heart disease, however, is proving to be controversial.
The KIF6 variant came to the attention of researchers when it was suggestively <a href="https://www.ncbi.nlm.nih.gov/pubmed?term=Five%20common%20gene%20variants%20identify%20elevated%20genetic%20risk%20for%20coronary%20heart%20disease.%20" target="_blank" rel="noopener noreferrer">linked to coronary heart disease</a> in 2007. Weak evidence for the association was also reported in a number of <a href="https://www.sciencedirect.com/science/article/pii/S0735109707034481" target="_blank" rel="noopener noreferrer">prospective studies</a> – people with at least one copy of the KIF6 variant, also called “carriers”, seemed to develop heart disease more than people without this version of the gene (non-carriers). Additional <a href="http://content.onlinejacc.org/cgi/content/short/51/4/449" target="_blank" rel="noopener noreferrer">studies</a> suggested that carriers receive greater benefit from statin therapy (pravastatin or atorvastatin) than non-carriers, but overall, none of these reports provided definitive statistical evidence for an association between the KIF6 variant and heart disease. 
 
Based on these initial reports, Celera, a biotechnology company that was involved in many of these studies, developed a <a href="http://kif6genotype.com/" target="_blank" rel="noopener noreferrer">genetic test</a> that determines whether a person has the KIF6 variant. This test was devised with the hope that it could pinpoint individuals who would derive the most benefit from statin therapy. Since as much as 60% of people with European ancestry carry at least one copy of this version of the KIF6 gene, millions of Americans with high LDL could potentially benefit from such a test. Although this version of the gene is also fairly common in African Americans and Asians, most of the research on KIF6 has been performed in people of European ancestry.
Although Celera filed for FDA clearance to market the test in early 2011, the application was <a href="http://www.genomeweb.com/dxpgx/fda-tells-celera-kif6-test-unapprovable-without-changes" target="_blank" rel="noopener noreferrer">rejected</a> because there wasn’t enough data to support its safety and effectiveness. This is in part because data surfaced in 2010 that contradicted the original reports. A large <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084526/?tool=pubmed" target="_blank" rel="noopener noreferrer">study</a> with 56,000 participants showed that people with the KIF6 variant do not suffer cardiac events more than non-carriers and another <a href="https://www.ncbi.nlm.nih.gov/pubmed/21458191">report</a> suggested that statin therapy had the same effect on carriers and non-carriers.
But like many research stories, there is now another twist. New findings published in <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0028834" target="_blank" rel="noopener noreferrer">PLoS One</a> by lead author Brian Ference confirmed that, on average, the KIF6 variant is not associated with heart disease risk, but then offered novel findings suggesting that people with the KIF6 variant are more vulnerable to the harmful effects of LDL and therefore may be at increased risk for heart disease. This study is the largest meta-analysis of KIF6 to date with 144,931 participants.
In Ference’s study, KIF6 carriers with very high LDL suffered more cardiac events than non-carriers with similar LDL levels and, conversely, carriers who lowered their LDL experienced greater protection from cardiac events compared to non-carriers who lowered their LDL to a similar degree. In addition, people with KIF6 variant benefited more from statin therapies than non-carriers. Carriers on statin therapy experienced a 27% reduction in heart disease risk per mmol/L decrease in LDL, while non-carriers on statin therapy experienced a 17% reduction per mmol/L decrease in LDL.
<img decoding="async" class="alignright size-full wp-image-11001" title="heart disease vs LDL" src="https://blog-api.23andme.com/wp-content/uploads/2012/02/heart-disease-vs-LDL.png" alt="" width="350" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/heart-disease-vs-LDL.png 613w, https://blogcms.23andme.com/wp-content/uploads/2012/02/heart-disease-vs-LDL-300x230.png 300w" sizes="(max-width: 613px) 100vw, 613px" />This figure shows a theoretical effect of a genetic variant on heart disease risk dependent on LDL levels. In the case of KIF6, the red line would correspond to carriers and the blue line to non-carriers. KIF6 carriers would exhibit increased heart disease risk than non-carriers at high LDL levels, but would also see a larger reduction in risk from lowering their LDL compared to non-carriers. (Figure adapted from Ference et al (2011).
These new findings add complexity to the story. They suggest that KIF6 carriers are more susceptible to heart disease risk conferred by high LDL levels but conversely derive greater benefit from lowering their LDL. These LDL-specific effects may help to explain why some of the early, small studies observed a possible link between the KIF6 variant and heart disease when the large study from 2010 – in people with a range of LDL levels – did not. Future studies may add even more clarity.
&nbsp;

Bethann Hromatka

KIF6 Tangos with LDL Cholesterol and Coronary Heart Disease

<a href="https://www.23andme.com/topics/ancestry/family-tree/">Every family has its stories</a>. We just don’t know them all. That’s where genealogy comes in. Through census and military records, notes in family bibles, or conversations with older relatives we can recover some of those family histories. But where memories and traditional paper records fail, we now have a new genealogical tool — our own DNA. The stories in PBS’ series “Finding Your Roots” illustrate the power of genetic genealogy and the use of DNA to solve family mysteries and uncover hidden stories.
<div style="float: right; text-align: justified; width: 300px; background-color: #eee; padding: 15px; margin-left: 10px; margin-bottom: 15px;"><a href="https://www.pbs.org/wnet/finding-your-roots/" target="_blank" rel="noopener noreferrer">Finding Your Roots</a> With Henry Louis Gates, Jr. is a 10-part series in which the Harvard scholar will delve into the genealogy and genetics of famous Americans. Gates uses history and science, including 23andMe’s ancestry tools, to explore race, family and identify in each episode. With the help from expert genealogists, historians and scientists –two of 23andMe’s own helped in the work – Gates reveals fascinating stories and interesting surprises in the family histories of Kevin Bacon, Robert Downey, Jr., Brandford Marsalis, John Legend, Martha Stewart, Barbara Walters and many others. 
23andMe’s Senior Director of Research, Joanna Mountain, is a geneticist who worked as a consultant on the series and was interviewed for a few of the episodes. Mountain, who completed her Ph.D. in Genetics at Stanford University, is also a guest blogger for the series. Her post below first appeared on the Finding Your Roots program page. We’re republishing it here with the permission of PBS.</div>
I’m a scientist. Mysteries and puzzles have always captivated me. For years I studied the fascinating riddle of human genetic diversity, working both at Stanford University and at the University of California, Berkeley to reconstruct human prehistory using DNA.
I knew the power of DNA to help us understand some of the most fundamental questions of human evolution, but it wasn’t until I applied the same science to my own family’s DNA that I saw how powerful it could be personally.
My own genealogical research started with a brownish-yellow, folded sheet of paper that was handed down to my father from his father. That piece of paper traced the history of the Mountain family back to 1755, just before a 5th great grandfather of mine changed his name from Mounton to Mountain. I was fascinated by how many children my ancestors had, and by how they kept reusing the same first names through the generations. I wondered who had made the effort to record, in such neat handwriting, all the names, birthdays, birthplaces and marriages. This faded piece of paper lent such importance to our family’s surname. We are The Mountains!
At the same time, as a professor of anthropological genetics at Stanford University, I was studying the ancestral lineages of people all over the world through DNA. I spent over 15 years studying the DNA of people in Tanzania, Sri Lanka, Italy, and many other far away places. My own use of genetic genealogy had to wait. It was only in 2007, when I began working for the personal genomics company, 23andMe, that I was able to turn my fascination with genetic variation to my own family. Now 15 of my family members and about two dozen of my husband’s family members have been tested.
<img loading="lazy" decoding="async" class="wp-image-11088 size-full alignright" title="MountainFamilyTreeTop" src="http://35.88.189.111/wp-content/uploads/2012/02/MountainFamilyTreeTop-scaled.jpg" alt="" width="2560" height="711" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-scaled.jpg 2560w, https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-300x83.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-768x213.jpg 768w, https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-1024x284.jpg 1024w, https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-880x244.jpg 880w, https://blogcms.23andme.com/wp-content/uploads/2012/02/MountainFamilyTreeTop-1180x328.jpg 1180w" sizes="auto, (max-width: 2560px) 100vw, 2560px" />
One of the first questions I tackled was the genetic lineage of the Mountain line. The challenge was that being female I don’t have a Y chromosome, which is essential for tracing the direct paternal line (from father, to father’s father, to father’s father’s father, and so on). The Y chromosome is one of the two sex chromosomes, the other being the X. Boys inherit a Y chromosome from their father and an X from their mother, while girls inherit an X chromosome from each parent. My father had passed away almost 20 years earlier, and I never had brothers. I knew of just one person with the same Y chromosome as my father — his brother, my uncle Peter in New Zealand. After hearing my pitch my uncle agreed to have his DNA tested. Just a few weeks later the results were in. I learned that my paternal lineage has the name of R1b1b2a1a1d*. Not so meaningful in itself, but this lineage is found mostly on the fringes of the North Sea in England, Germany and the Netherlands, having belonged to residents of Doggerland, a low lying region of forests and wetlands that must have been rich in game… between 9000 and 12,000 years ago. So that’s where the Mountain line originated!
There is no yellowed piece of paper with beautiful handwriting handed down in my mother’s family. In fact, five years ago I knew little more than my maternal grandparents’ names. So I began asking my mother and aunt a few questions. And I checked my results. There is one type of DNA, mitochondrial DNA that all people have, but that is passed down only from mother to child. DNA in the sections of our cells called mitochondria enables us to trace our direct maternal line (from mother, to mother’s mother, to mother’s mother’s mother, and so on) just like the Y chromosome allows people to trace the paternal line. My maternal DNA lineage is called H10a1. This lineage marks a special connection among the group that includes my mother, my sisters and our children. My boys won’t pass on this lineage, but hopefully my niece will have a daughter one day!
The “H” refers to a maternal lineage that originated in the Near East and then expanded, following the decline of the last Ice Age, into Europe, where it is the most prevalent lineage today. Even Marie Antoinette had this lineage! But there are no published details regarding the sub lineage called H10, shared by far fewer individuals than H. To learn more I turned to other colleagues with the H10 lineage. Some, like me, said they trace their ancestry to the United Kingdom. But many more trace ancestry to eastern Europe — Ukraine and Russia. So could my mother’s ancestry trace back to eastern Europe? This was a possibility I had never before fathomed!
Learning my own family’s ancestry connected me to the broader expanse of human history. My DNA not only confirmed what I knew about my English, Irish and Scottish roots, but also revealed deeper roots than I ever imagined along the rim of the North Sea, and a possible newfound link to eastern Europe. As someone, like many Americans, who is far removed from my ancestral homelands, the information connected me to those places. Now I had ancestral stories.
But my family extends beyond my parents and me. I have a husband and two sons, and looking at their DNA added detail and nuance to our family’s story. When we first looked at my husband’s results I thought they were wrong. The results just didn’t fit with what we knew. His family traced ancestry to England, Ireland and Switzerland, but his results pointed to something we hadn’t known about, Native American ancestry on his maternal line. The result spurred my husband to dig more deeply into his maternal line, which is typically more challenging than the paternal line because surnames change each generation. Lo and behold, he found records suggesting that his 6th great grandmother was of mixed ancestry. His South Carolina roots trace not just to European settlers, but also to ancestors living in the Americas 10,000 or more years ago.
Personal genetic information allows you to look not just at your ancient ancestors, but also at very recent connections. One of my favorite moments in this exploration of our family’s genetic genealogy came when my husband and I found some time one evening to show our boys their data. My husband has hazel eyes and mine are brown, but both our sons have blue eyes. It turns out that my husband and I each carry one copy of the “blue” version of an eye color gene, and both of us passed on that version to both boys (one chance in 16!).
<img loading="lazy" decoding="async" class="alignright wp-image-11057 size-medium" title="AnthonyRobertMountain" src="http://35.88.189.111/wp-content/uploads/2012/02/AnthonyRobertMountain-200x300.jpg" alt="" width="200" height="300" srcset="https://blogcms.23andme.com/wp-content/uploads/2012/02/AnthonyRobertMountain-200x300.jpg 200w, https://blogcms.23andme.com/wp-content/uploads/2012/02/AnthonyRobertMountain.jpg 426w" sizes="auto, (max-width: 200px) 100vw, 200px" />
Because my mother had also been tested, we could see that the boys had inherited the blue version from my father, who died almost 23 years ago. So my sons got their blue eyes from my father, the grandfather they never met, who had passed on the genetic variant through me to both of them. When we made this discovery, I quickly looked around for a photo of my dad, finding a tiny one on the office wall. I pointed it out to my younger son, who exclaimed, “Grandpa!” Knowing he had received something in particular from his grandpa strengthened his connection to the man he didn’t know otherwise. And for all of us it added another page to our family’s story.
Joanna Mountain is a geneticist who is a consultant to the PBS series “Finding Your Roots,” and consulted previously on the PBS series “Faces of America.” Dr. Mountain completed her PhD in Genetics at Stanford University and has spent over 20 years studying human genetic diversity. Currently, she is Senior Director of Research at <a href="https://www.23andme.com/" target="blank" rel="noopener noreferrer">23andMe, Inc.</a>

Stories on Every Branch of the Family Tree

In December a new study created quite a stir in the already-volatile clopidogrel research community. Clopidogrel (trade names Plavix ®) is a commonly prescribed anti-clotting drug. It is inactive in the body until a protein encoded by the gene CYP2C19 converts the drug to its active form. Some people are able to make this conversion more quickly and effectively than others, partially due to genetic mutations in the CYP2C19 gene. How this ability to process clopidogrel impacts a patient’s risk of heart attack and other cardiac events, however, is unclear. Are slow metabolizers (those who can not convert clopidogrel to the active form very well) at higher risk for cardiac events than fast metabolizers?
Many researchers and physicians, based upon the results of recent studies, believe that slow metabolizers of clopidogrel do, in fact, receive less protective benefit from the drug. The evidence for an association between CYP2C19 genotype and cardiac events was perceived to be so strong that, in March of 2010, the <a href="https://blog.23andme.com/articles/fda-adds-boxed-warning-to-plavix-label-to-highlight-reduced-effectiveness-of-the-drug-in-poor-metabolizers" target="_blank" rel="noopener noreferrer">FDA added a boxed warning</a> on the drug labeling for clopidogrel asserting that slow metabolizers of the drug may need “alternative treatments” to avoid heart attacks and other cardiovascular events. Others, however, are less convinced that being able to process clopidogrel quickly actually translates to improved protection against cardiac events. After the FDA released their boxed warning, the American College of Cardiology and the American Heart Association <a href="https://www.ncbi.nlm.nih.gov/pubmed/20585015" target="_blank" rel="noopener noreferrer">published a report</a> maintaining that routine genetic testing for CYP2C19 mutations for the purpose of clopidogrel dosing was not justified by the current research.
Last month Dr. Michael Holmes and a team of researchers from the University College London published a study in the Journal of the American Medical Association stating that although CYP2C19 genotypes affect how quickly one processes clopidogrel, it does not actually affect one’s risk of cardiovascular events. After analyzing results from 32 previously published studies relating clopidogrel and CYP2C19 genotype, they determined that there was likely no true association.

Of particular note to Holmes and his colleagues was the fact that the studies reporting the strongest associations between CYP2C19 metabolizer status and cardiovascular outcomes were also the smallest, perhaps reflecting the tendency for small research groups to publish only positive findings (publication bias). The type of study also seemed to matter &#8212; the preferred, but less common case-control studies were less likely to show an association than the treatment-only studies. The researchers concluded that there is likely no statistically significant association between CYP2C19 genotype and cardiovascular events, although they briefly concede that the specific complication of stent thrombosis might be a &#8220;possible exception.&#8221;
Some scientists, such as Dr. Steven Nissen, have applauded this new meta-analysis. In Dr. Nissen’s editorial “Pharmacogenomics and Clopidogrel: Irrational Exuberance?”, he calls the analysis results “compelling.” Other experts in the field, however, were less enthusiastic about the new study. Dr. Eric Topol, the director of Scripps Translational Science Institute, responded with a rebuttal in his blog, criticizing the study for failing to correctly account for type of treatment and for including patients for whom the benefit of clopidogrel is not well established.
Dr. Topol argues that clopidogrel is useful for preventing clotting in patients who have been treated with stents, and that this is one of the primary uses of the drug. Dr. Topol criticizes the authors for downplaying the association between CYP2C19 genotype and stent thrombosis and their failure to highlight the importance of CYP2C19 genotyping for stent-treated patients. In the study’s combined analysis, both stent-treated patients and patients treated by other means (for whom the benefit of clopidogrel is less established) were included. If clopidogrel does not significantly lower the risk of cardiac events in non-stent patients, then the non-stent patients included in the analysis would make it difficult to observe an association between genotype and cardiac events. Dr. Topol called the failure to control for treatment type a “critical flaw” in the analysis and asserted that the study was “remarkably misleading.”
Certainly, the last word in the clopidogrel debate has not yet been spoken. This study and the ongoing discussion, however, illustrate many of the challenging issues surrounding pharmacogenetic research. Publication bias, inadequate scientific controls, and the difficulty in translating genetic discoveries into clinical outcomes are all obstacles we will need to hurdle to realize the benefits of personalized medicine.

The Debate Over Clopidogrel Continues

<img decoding="async" class="alignright size-full wp-image-8873" title="elderly" src="https://blog-api.23andme.com/wp-content/uploads/2011/04/elderly.jpg" alt="" width="300" srcset="https://blogcms.23andme.com/wp-content/uploads/2011/04/elderly.jpg 350w, https://blogcms.23andme.com/wp-content/uploads/2011/04/elderly-300x223.jpg 300w" sizes="(max-width: 350px) 100vw, 350px" />
With analytical contributions from 23andMe Scientist David Hinds
For all human history people have been obsessed with their own mortality. Early explorers searched the globe for the mythical “fountain of youth,” and now scientists are turning that exploration inward to look at the genomes of people who’ve lived especially long lives.
Longevity runs in families, which suggests that the reason some people live longer than others has something to do with genetics. Indeed, <a href="https://www.ncbi.nlm.nih.gov/pubmed/17903295" target="_blank" rel="noopener">some studies</a> have identified a few genetic variants that occurred more frequently in people who live to be at least 95 years old, for example <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2544566/" target="_blank" rel="noopener">this small study in Japanese men</a>. These few variants, however, don’t seem to contribute significantly to whether someone will live to be 100.
Larger studies looking broadly across the genome for common variants contributing to longevity have mostly come up empty. A <a href="http://biomedgerontology.oxfordjournals.org/content/65A/5/478" target="_blank" rel="noopener">four-study combined analysis</a> published two years ago found no significant associations between common SNPs and longevity, and an initially more promising study published by Paola Sebastiani and Thomas Perls from Boston University was later <a href="http://retractionwatch.wordpress.com/2011/07/21/sebastiani-group-retracts-genetics-of-aging-study-from-science/" target="_blank" rel="noopener">retracted</a> due to <a href="https://blog.23andme.com/articles/snpwatch-uncertainty-surrounds-longevity-gwas" target="_blank" rel="noopener">problems with the analysis</a>.
Explorations of lifestyle factors impacting longevity have also turned up somewhat conflicting results. Most studies indicate that those who live longer have <a href="https://www.ncbi.nlm.nih.gov/pubmed/18268169" target="_blank" rel="noopener">healthier diets, exercise more and experience delayed onset of disease</a>, perhaps due to their healthier lifestyles. Smoking seems to lower one’s chances of living longer. Maintaining a healthy weight may also be associated with <a href="https://www.ncbi.nlm.nih.gov/pubmed/21252546" target="_blank" rel="noopener">better cognitive function</a> and lower risk of dementia. But other studies have found <a href="https://www.ncbi.nlm.nih.gov/pubmed/21812767" target="_blank" rel="noopener">no difference</a> in BMI or diet between long-lived individuals and the average population, suggesting that many other factors are involved.
Despite its elusiveness, the quest to uncover the secrets of longevity continues. As more people live longer, larger studies of the super long-lived will become more feasible. The <a href="http://www.bumc.bu.edu/supercentenarian" target="_blank" rel="noopener">New England Supercentenarian Study</a> led by Boston University, for example, now consists of more than 60 people over the age of 110. Many of these individuals maintain <a href="http://nymag.com/news/features/ashkenazi-jews-2011-11/" target="_blank" rel="noopener">physical independence and mental acuity</a> well past the age of 100. By analyzing the DNA, lifestyle habits, and environmental surroundings of these extremely long-lived people, the researchers hope to learn about genetic as well as non-genetic factors contributing to longevity.
Unfortunately, their most recent findings &#8212; a pair of papers authored by the same group (Sebastiani and Perls) whose paper was retracted last year &#8212; contain little that can be generalized and have methodological shortcomings that call into question the conclusions they do make.
In the first study, an <a href="http://www.frontiersin.org/Genetics_of_Aging/10.3389/fgene.2011.00090/abstract" target="_blank" rel="noopener">analysis of the genomes of two supercentenarians</a>, Sebastiani and Perls suggest that the male supercentenarian’s extreme longevity may be due to an excess of common variants linked to longevity. They base this on the man’s enrichment for a set of previously identified longevity-associated genetic variants but without taking into account the fact that many of the variants in that set are correlated with each other. They also point to his high score on the predictive model described in their second paper, a result that is less surprising considering that the man’s data was used to develop that model in the first place. Several other of their conclusions also appear to be over-interpreted.
<img loading="lazy" decoding="async" class="alignleft size-medium wp-image-6445" title="elderly_1" src="https://blog-api.23andme.com/wp-content/uploads/2010/04/elderly_1-300x199.jpg" alt="" width="300" height="199" srcset="https://blogcms.23andme.com/wp-content/uploads/2010/04/elderly_1-300x199.jpg 300w, https://blogcms.23andme.com/wp-content/uploads/2010/04/elderly_1.jpg 425w" sizes="auto, (max-width: 300px) 100vw, 300px" />
A close reading of Sebastiani and Perls’ other paper (the <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0029848" target="_blank" rel="noopener">republished version of their previous retraction</a>) reveals that the number of genetic variants that they identified for their model is actually quite close to the number of expected false positives (the authors misreport the number of expected false positives by a factor of 10). This means that many of the genetic variants that they suggest are associated with longevity are likely not to be associated with longevity at all. The model’s predictive accuracy is also very high when applied to the training data, but much lower when applied to individuals that were not included in the training set, suggesting that the model does not generalize well.
Studies like these certainly hint at the potential discoveries we could make from analyzing the genomes of people who live to be 100 or older. Can we identify common genetic variation predictive of longevity? Do rarer variants play a role? What genes and pathways are important? Ultimately, however, the latest foray into the genetics of longevity raises more questions about methodology and interpretation than satisfying answers or hypotheses. It appears the secrets of the super long-lived will remain secret for now.

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