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A conversation about using genetics to advance cardiovascular medicine

A conversation about using genetics to advance cardiovascular medicine

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In recognition of American Heart Month, Stanford Health Care is hosting a heart fair on Saturday. The free community event includes a number of talks ranging in topic from the latest developments in treating atrial fibrillation to specific issues related to women’s heart health.

During the session on heart-disease prevention, Joshua Knowles, MD, PhD, will deliver a talk titled “How We Can (and Will) Use Genetics to Improve Cardiac Health.” Knowles’ research focuses on familial hypercholesterolemia, a genetic disease that causes a deadly buildup of cholesterol in the arteries. He and colleagues recently launched a project that uses a big-data approach to search electronic medical records and identify patients who may have the potentially fatal heart condition.

To kick off the conversation about preventing heart disease, I contacted Knowles to learn more about how the genomics revolution is changing the cardiovascular medicine landscape and what you can do to determine if you have a genetic heart disorder. Below he explains why heart disease is a “complex interplay between genetics and environment” and what the future may hold with respect to personalized treatments and pharmacogenetics.

Let’s start by talking about your work on familial hypercholesterolemia (FH). How has the understanding of the genetic basis of FH evolved over the last few years, and what key questions remain unanswered?

For FH, there has been a revolution in our understanding. FH causes very elevated cholesterol levels and risk of early onset heart disease. We used to think that it affected 1 in 500 individuals, but recent studies have pointed out that this is probably an underestimate and it may affect as many as 1 in 200 people. This means that there may be as many as 1 million people in the United States who are affected. We have also identified new genes that cause FH, and the identification of some of these genes has directly translated into the development of a new class of drugs (so called PCSK9 inhibitors) to treat this condition.

What steps can patients take to determine if they are at risk of, or may have, a genetic cardiovascular disorder like FH?

The easiest way is to know about your family history of medical conditions- to know what illnesses affected parents, grandparents, uncles, aunts and other relatives. Of course, genes aren’t the only things that are passed in families. Good and bad habits, such as exercise patterns, smoking and diet, are also passed down through the generations. But a family history of heart disease or certain forms of cancer is certainly a risk factor.

Past research suggests that patients with a genetic predisposition to heart disease can significantly reduce their chances of having a heart attack or stroke by making changes to their lifestyle, such as eating a diet rich in fruits and vegetables. Can lifestyle changes overcome genetics?

Heart disease is a result of the complex interplay between genetics and environment – lifestyle, for instance. For some people with specific genetic conditions, such as familial hypercholesterolemia or hypertrophic cardiomyopathy, the effect of genetics tends to dominate the effect of environment because the genetic effect is so large.

For the vast majority of people without these “Mendelian” forms of heart disease, which follow the laws of inheritance were derived by nineteenth-century Austrian monk Gregor Mendel, it’s difficult to determine at an individual level how much of the risk is due to genes and how much is due to environment (this is for things like high blood pressure, high cholesterol, coronary disease). One clue is certainly family history. However, for most of these diseases the genes are not “deterministic” – that is, people are not destined to have these diseases. Some are more at risk than others, but there are certainly ways to mitigate genetic risk through lifestyle choices. Choosing not to smoke and exercising regularly are two examples of ways you can help to greatly minimize genetic risk.

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Cancer, Evolution, Genetics, Infectious Disease, Microbiology, Research, Stanford News

Bubble, bubble, toil and trouble – yeast dynasties give up their secrets

Bubble, bubble, toil and trouble - yeast dynasties give up their secrets

yeasty brew

Apologies to Shakespeare for the misquote (I’ve just learned to my surprise that it’s actually “Double, double, toil and trouble“), but it’s a too-perfect lead-in to geneticist Gavin Sherlock’s recent study on yeast population dynamics for me to be bothered by facts.

Sherlock, PhD, and his colleagues devised a way to label and track the fate of individual yeast cells and their progeny in a population using heritable DNA “barcodes” inserted into their genomes. In this way, they could track the rise and fall of dynasties as the yeast battled for ever more scarce resources (in this case, the sugar glucose), much like what happens in the gentle bubbling of a sourdough starter or a new batch of beer.

Their research was published today in Nature.

From our release:

Dividing yeast naturally accumulate mutations as they repeatedly copy their DNA. Some of these mutations may allow cells to gobble up the sugar in the broth more quickly than others, or perhaps give them an extra push to squeeze in just one more cell division than their competitors.

Sherlock and his colleagues found that about one percent of all randomly acquired mutations conferred a fitness benefit that allowed the progeny of one cell to increase in numbers more rapidly than their peers. They also learned that the growth of the population is driven at first by many mutations of modest benefit. Later generations see the rise of the big guns – a few mutations that give carriers a substantial advantage.

This type of clonal evolution mirrors how a bacterium or virus spreads through the human body, or how a cancer cell develops mutations that allow it to evade treatment. It is also somewhat similar to a problem that kept some snooty 19th century English scientists up at night, worried that aristocratic surnames would die out because rich and socially successful families were having fewer children than the working poor. As a result, these scientists developed what’s known as the “science of branching theory.” They described the research in a paper in 1875 called “On the probability of extinction of families,” and Sherlock and his colleagues used some of the mathematical principles described in the paper to conduct their analysis.

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Genetics, In the News, LGBT, Medicine and Society, Research, Sexual Health

Sex biology redefined: Genes don’t indicate binary sexes

Sex biology redefined: Genes don't indicate binary sexes

14614853884_3d6d1d662a_zImagine being a forty-six-year-old woman pregnant with her third child, whose amniocentesis follow-up shows that half her cells carry male chromosomes. Or a seventy-year-old father of three who learns during a hernia repair that he has a uterus. A recent news feature in Nature mentioned these cases as it elaborated on the spectrum of sex biology. People can be sexed in a non-straightforward way and not even be aware of it; in fact, most probably aren’t. As many as 1 person in 100 has some form of “DSD,” a difference/disorder of sex development.

The simple scenario many of us learned in school is that two X chromosomes make someone female, and an X and a Y chromosome make someone male. These are simplistic ways of thinking about what is scientifically very complex. Anatomy, hormones, cells, and chromosomes (not to mention personal identity convictions) are actually not usually aligned with one binary classification.

The Nature feature collects research that has changed the way biologists understand sex. New technologies in DNA sequencing and cell biology are revealing that chromosomal sex is a process, not an assignation.

As quoted in the article, Eric Vilain, MD, PhD, director of the Center for Gender-Based Biology at UCLA, explains that sex determination is a contest between two opposing networks of gene activity. Changes in the activity or amounts of molecules in the networks can sway the embryo towards or away from the sex seemingly spelled out by the chromosomes. “It has been, in a sense, a philosophical change in our way of looking at sex; that it’s a balance.”

What’s more, studies in mice are showing that the balance of sex manifestation can be shifted even after birth; in fact, it is something actively maintained during the mouse’s whole life.

According to the Nature feature, true intersex disorders, such as those from divergent genes or the inability of cellular receptors to respond to hormones, yield conflicting chromosomal and anatomical sex. But these are rare, about 1 in 4,500. For the 1/100 figure, they used a more inclusive definition of DSDs. More than 25 genes that affect sex development have now been identified, and they have a wide range of variations that affect people in subtle ways. Many differences aren’t even noticed until incidental medical encounters, such as in the opening scenarios (the first was probably caused by twin embryos fusing in the woman’s mother’s womb; the second by a hormonal disorder).

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Applied Biotechnology, Bioengineering, Cancer, Genetics, Research, Stanford News

Minuscule DNA ring tricks tumors into revealing their presence

Minuscule DNA ring tricks tumors into revealing their presence

cool minicirclesAn animal study just published in Proceedings of the National Academy of Sciences shows how, in the not-distant future, doctors may be able to not only detect tumors early in humans, but also monitor the effectiveness of cancer drugs in real time, guide clinical trials of new drugs, and even screen entire populations of symptom-free people for nascent tumors that could have otherwise slipped under the radar.

The potential is huge. And the principal investigator, Sam Gambhir, MD, PhD, is credible: He chairs Stanford’s radiology department, directs the Canary Center at Stanford for Cancer Early Detection and has authored or co-authored nearly 600 peer-reviewed research publications.

From my news release about the study:

Imagine: You pop a pill into your mouth and swallow it. It dissolves, releasing tiny particles that are absorbed and cause only cancerous cells to secrete a specific protein into your bloodstream. Two days from now, a finger-prick blood sample will expose whether you’ve got cancer and even give a rough idea of its extent. That’s a highly futuristic concept. But its realization may be only years, not decades, away.

The key to early cancer detection lies in finding valid biomarkers: substances whose presence in a person’s blood or urine flags a probable tumor. (High blood levels of the molecule known as PSA, for example, can signify prostate cancer.) But although various tumor types indeed secrete characteristic substances into the blood, these same substances typically are made in healthy tissues, too, albeit usually in smaller amounts. So a positive test result for, say, PSA doesn’t necessarily mean the person has cancer. Contrariwise, a small tumor just may not secrete enough of the trademark substance to be detectable.

Gambhir’s team appears to have found a way to force any of numerous tumor types to produce a biomarker whose presence in the blood unambiguously signifies cancer, because no adult tissues – cancerous or otherwise – would normally be making it. This particular substance is a protein naturally present in human embryos as they’re forming and developing, but absent in adults.

The scientists designed a genetic construct, called a DNA minicircle, that contains a single gene coding for the telltale substance. DNA minicircles are tiny, artificial, single-stranded DNA rings about 4,000 nucleotides in circumference – roughly one-millionth as long as the strand that you’d get if you stretched the DNA in all 23 chromosomes of the human genome end to end.

Gambhir and his colleagues rigged their minicircles so that this sole gene would be “turned on” only inside cancer cells. (For more details on how to do this, please see my release.) They injected the minicircles into mice who had small tumors and mice who didn’t. Within 48 hours, a simple blood test indicated the presence of the biomarker in the blood of mice with tumors, but not in the blood of the tumor-free mice.The bigger the tumor volume, the more of the biomarker in the blood.

The technique will likely apply to a broad range of cancers, and can possibly be modified to help pinpoint budding tumors’ location in the body.

Previously: Nano-hitchhikers ride stem cells into heart, let researchers watch in real time and weeks later, Nanoparticles home in on human tumors growing in mice’s brains, increase accuracy of surgical removal and Nanomedicine moves one step closer to reality
Photo by Jim Strommer

Aging, Genetics, In the News, Mental Health, Neuroscience, Research, Women's Health

Are women at greater risk for Alzheimer’s? Stanford expert to discuss on today’s Science Friday

Are women at greater risk for Alzheimer’s? Stanford expert to discuss on today's Science Friday

2187905205_158290644d_zConfession: I named my parents’ cat (who died recently) Watson after listening to Ira Flatow interview James Watson, PhD, while driving cross country with my dad in 2000. Both before and after the all-critical cat-name-inspiring program, Science Friday has been a part of my Friday as often as I can squeeze it in.

So I was happy to hear that today’s program (which airs locally from 11 a.m. to 1 p.m. on KQED) will feature Stanford’s Michael Greicius, MD, MPH. He’ll be talking about Alzheimer’s disease and why the disease affects men and women differently.

Greicius, medical director of the Stanford Center for Memory Disorders, has worked with the gene variant known as ApoE4 – the largest single genetic risk factor for Alzheimer’s, particularly for women. Last spring, he published a study showing that healthy ApoE4-positive women were twice as likely to contract the disease as their ApoE4-negative counterparts.

Greicius is expected to be on in the second hour, from 12 to 1 p.m. Pacific time.

Previously: Blocking a receptor on brain’s immune cells counters Alzheimer’s in mice, Examining the potential of creating new synapses in old or damaged brains, The state of Alzheimer’s research: A conversation with Stanford neurologist Michael Greicius and Having a copy of ApoE4 gene variant doubles Alzheimer’s risk for women but not for men
Photo by *Ann Gordon

Big data, Genetics, Global Health, Infectious Disease, Research, Science

The benefit of mathematical models in medicine

The benefit of mathematical models in medicine

1024px-Free_range_chicken_flockTheoretical modeling sounds like it has, at best, a distant connection to the day-to-day concerns of medical professionals who care for or research the needs of patients. But when I spoke recently with Noah Rosenberg, PhD, a population geneticist at Stanford and editor of the scientific journal Theoretical Population Biology, he pointed out that modeling can offer distinct benefits to those in medical fields like epidemiology and genetics.

“We see a lot of occasions in public discussions of areas like the spread of epidemics, the demography of aging populations, and big data analysis in genomics where part of the backdrop arises from theoretical population biology work,” Rosenberg said. “We hope to spread the word that there is a place for the kinds of theoretical and mathematical insights that can contribute to those important topics.”

Rosenberg noted that papers in the journal often span the divide between mathematics and biology, but they have a few things in common. In an editorial he published last month in the journal, Rosenberg describes an ideal study for the journal – namely that first, “the mathematical work is motivated by a genuine problem in biology, and there’s a need for theory to resolve the problem,” he said. Secondly, the mathematical work is substantial enough that it uncovers new potential relationships or new explanations for a phenomenon, and lastly, that the advances contribute to our understanding of biology – though some of the best papers in the field can also have a big impact on the field of mathematics, too.

When I asked him to talk about what that would mean for studies that touch on health research, he pointed me to a couple of fascinating papers. One is a paper by Shai Carmi, PhD, and colleagues that explains a new way to look at shared DNA strands between people in order to understand their relatedness and the amount of overlap in their genomes. This has implications for how we think about “the way in which genes descend within families, including genes that may be related to a disease.” It’s one of the journal’s most downloaded papers, Rosenberg told me.

The second is a study by Maciej Boni, PhD, and colleagues that incorporates how decisions that poultry farmers in Southeast Asia make about market conditions might affect the spread of avian influenza in their flocks. When avian flu is identified in a region, poultry flocks are usually culled. It’s an interesting example of how human behavior can affect disease dynamics.

Rosenberg noted that the studies and models that are able to incorporate human behavioral patterns are among the most interesting that he sees. Nailing down how people’s decisions affect the course of an outbreak is notoriously difficult, but like the avian influenza paper demonstrates, mathematical models make it possible to explore the consequences of different assumptions about these decisions.

Rosenberg says that it’s even possible to make mathematical models of cultural practices (like deciding not to immunize your children) and how they spread among groups of people. One public laboratory this interaction is currently playing out in is the measles outbreak that got its start at Disneyland in December. The outbreak topped 100 cases nationwide, mostly among families that refuse to vaccinate their children. “It’s the intersection between human behavior and dynamics of disease,” he said. “Putting those together in a mathematical model to predict what might happen is the kind of work that appears in Theoretical Population Biology.”

Previously: Stanford physician Sanjay Basu on using data to prevent chronic disease in the developing world and Facebook app models how viruses spread through human interaction
Photo by Woodley Wonderworks

Genetics, NIH, Research, Science, Stanford News

Project Roadmap: Mysteries of the epigenome revealed

Project Roadmap: Mysteries of the epigenome revealed

Let’s hear it for large, international collaborations! Hot on the heels of the ENCODE Project (well, in research time anyway) comes the National Institutes of Health’s Roadmap Epigenomics Project, which is geared toward understanding how chemical tags on DNA and its associated proteins determine how each cell uses the information in the genome to develop its own identity. One of the leaders of the massive project was geneticist Anshul Kundaje, PhD, who helped to analyze the huge amounts of data generated by labs around the world as they studied more than 100 adult and fetal human tissues.

The work is published today in Nature in the form of a large package of papers. Kundaje is the first author of the main paper; Nature has also published a nice summary of all the papers in the issue and produced a musical video to explain the project.

From our release:

The problem [of picking and choosing from a genome’s worth of information] is somewhat like being handed a list of all the ingredients available in a well-stocked kitchen without any idea of how to combine them. Tossing a few of them together, willy-nilly, into a baking dish and popping it into the oven isn’t likely to yield anything edible. But with a well-written recipe telling you how much and when to mix together flour, sugar, eggs and butter, you can turn out a perfect cake or fantastic waffles.

The completion of the Human Genome Project gave biologists the list of ingredients to which every cell has access. The Roadmap Epigenomics Project outlines the recipes and shows how cells use these ingredients to generate their own special sauce. By comparing and contrasting these cellular recipes, researchers can begin to draw parallels among cell types and even predict which cells might be involved in specific traits and diseases.

As a proof of principle, Kundaje and others showed in one of the companion papers that, based on the epigenomic maps shared among cells, the immune system is likely to play a larger role in the development of Alzheimer’s disease than previously thought.

Previously: Scientists announce the completion of the ENCODE project, a massive genome encyclopedia , Red light, green light: Simultaneous stop and go signals on stem cells’ genes may enable fast activation, provide “aging clock” and Caught in the act! Fast, cheap, high-resolution, easy way to tell which genes a cell is using

Genetics, Research, Stanford News

The needle in the haystack: identifying gene function

The needle in the haystack: identifying gene function

To answer big questions in science, sometimes you have to go big. More than a decade ago, the human genome was sequenced in its entirety. To gain perspective on how big a question the sequence of our genome was, consider this: If you lined up human DNA, it could reach the sun and back… six times!

Knowing the sequence of genes isn’t everything though, and approximately one-third of our genome (or about 6,000 genes) has unknown or poorly characterized function.

Researchers at Stanford, led by Tobias Meyer, PhD, professor of cell biology, and graduate student Gautam Dey developed a comparative search engine to help identify the function for a small group of genes. The study was published online Feb. 12 in Cell Reports, and the search engine is accessible here.

“After the human genome was sequenced, scientists thought it would be a very short time before we knew what all the genes are doing,” Meyer told me. “It turned out not to be so easy, and we are currently in a holding pattern before we can really make use of all the genomic information.”

Having a starting point for identifying a gene’s function is important. Otherwise, it can be like searching for a needle in a haystack, as I wrote in a story on the paper:

To computationally identify the function of a gene, scientists have a few options. The easiest is finding another human gene with a similar sequence for comparison. Another option is searching for human genes with shared ancestry for comparison. But sometimes there is no human gene available for comparison, and scientists have to compare human genes to those from other species.

The search engine relies on accessing genomic sequences from humans and other species that are contained in the RefSeq online database and then narrows the myriad of possible starting points for identifying human gene function. This study is an example of using freely available big datasets to make it easy for scientists to ask and answer difficult questions, which is a current trend spanning the biological sciences.

Kimberlee D’Ardenne is a writing intern in the medical school’s Office of Communication and Public Affairs.

Previously: Open source encyclopedia of human genome’s functional elements in the works, Of mice and men: Stanford researchers compare mammal’s genomes to aid human clinical research and DNA origami: How our genomes fold

 

Genetics, In the News, Medicine and Society, Research, Science, Technology

A leader in the Human Genome Project shares tale of personalized medicine, from 1980 until today

A leader in the Human Genome Project shares tale of personalized medicine, from 1980 until today

2559447601_005b33ae7d_zEric Lander, PhD, warned the several hundred people who came to hear him speak on the Stanford campus earlier this week that he wasn’t giving a traditional data-packed scientific presentation.

Instead, the founding director of the Broad Institute and veteran of the Human Genome Project — who Google’s Eric Schmidt introduced — promised to tell a story, a yarn about, as he put, the biomedicine of the East Coast meeting the technological innovation of the West Coast. (He couched the statement and admitted that yes, the West Coast does have a bit of biomedicine.)

So here goes:

Once upon a time, 35 years ago, in a land ruled by punk rock and big hair, scientists worked hard to pinpoint the genetic cause of cystic fibrosis, a disease caused by a single mutation. It was slow, hard work, but they persevered and found the gene.

Wouldn’t it be wonderful to know all the human genes, some scientists speculated, buoyed by their preliminary success. Cancer could be vanquished. Genetic disorders a thing of the past. But getting to that point might take as long as 2,000 years.

Enter the Human Genome Project (HGP) in 1990. A collaborative effort of 16 research centers in six countries, the team “industrialized biology,” cranking out a code for the 3 billion base pairs that make up the human genome.

Of equal importance, the HGP was advocating the importance of public access to genetic material. It faced a challenge from a rival private company, Celera, who proposed creating a subscription database with the genetic information.

The HGP also had to contend with hype, Lander said: With a banner-headline, the New York Times had proclaimed in 2000 “Genetic code of human life is cracked by scientists.”

But really, the scientists had little more than a gigantic text — ATCGGCTATATAATCG — that Lander likened to the Rosetta Stone. By comparing it with the genomes of mice, dogs, rats, cats, dolphins and many other critters, scientists worldwide were able to decipher it piece by piece.

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Aging, Genetics, Research, Science, Stanford News

My funny Valentine – or, how a tiny fish will change the world of aging research

My funny Valentine - or, how a tiny fish will change the world of aging research

YoungFishI admit it. I have crush on a fish. The object of my affection is the African turquoise killifish – a tiny, colorful fish that lives in seasonal ponds and puddles under the hot sun of Mozambique and Zimbabwe. Because the pools dry out regularly, the fish have evolved to have a normal lifespan of only a few months. In fact, it’s one of the shortest-lived vertebrates known. It’s also zippy, territorial and (maybe it’s just me?) seemingly possessing a degree of chutzpah noticeably absent in your average goldfish.

The killifish’s compressed lifespan, plus the ease and speed with which it can be housed and bred, make it an ideal model for genetic studies of aging and longevity. But in the absence of a fully sequenced genome and little information about gene expression patterns or a way to introduce selective mutations, it’s been difficult for researchers to get a scientific handle on the slippery creature.

Today, geneticists Anne Brunet, PhD, and Itamar Harel, PhD, published a comprehensive genetic toolbox for use by researchers around the world wanting to draw parallels between humans and my tiny, finned crush. The article appears online in Cell; a charming video abstract describing their work is also available.

As I describe in our release:

Although the similarities between fish and humans may not be immediately evident, people have much more in common with the tiny, minnowlike creature than with other short-lived laboratory animals.

“This fish gives us the best of both worlds,” said postdoctoral scholar Itamar Harel, PhD. “As a vertebrate, it shares many critical attributes with humans, including an adaptive immune system, real blood and similar stem cell biology.

At the same time, its very short life span mimics those of the laboratory worms, yeast and fruit flies that until now have served as the traditional models of aging research.”

A short life span allows researchers to quickly assess the effect of genetic variations among different strains of fish. It also allows them to breed and raise hundreds of progeny for study within the span of months, rather than the many years required to conduct similar experiments in other vertebrates.

“The life span of a mouse can be as long as three to four years,” said Anne Brunet, PhD, professor of genetics. “This is close to the average length of a postdoctoral or graduate student position. This means that it would be very difficult for a researcher to conduct a meaningful analysis of aging in the mouse within a reasonable time period.”

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