Every Cell in Your Body Has the Same DNA. Except It Doesn’t.

ames Priest couldn’t make sense of it. He was examining the DNA of a desperately ill baby, searching for a genetic mutation that threatened to stop her heart. But the results looked as if they had come from two different infants.

“I was just flabbergasted,” said Dr. Priest, a pediatric cardiologist at Stanford University.

The baby, it turned out, carried a mixture of genetically distinct cells, a condition known as mosaicism. Some of her cells carried the deadly mutation, but others did not. They could have belonged to a healthy child.

We’re accustomed to thinking of our cells sharing an identical set of genes, faithfully copied ever since we were mere fertilized eggs. When we talk about our genome — all the DNA in our cells — we speak in the singular.

But over the course of decades, it has become clear that the genome doesn’t just vary from person to person. It also varies from cell to cell. The condition is not uncommon: We are all mosaics.

For some people, that can mean developing a serious disorder like a heart condition. But mosaicism also means that even healthy people are more different from one another than scientists had imagined.

Magical Mystery

In medieval Europe, travelers making their way through forests sometimes encountered a terrifying tree.

A growth sprouting from the trunk looked as if it belonged to a different plant altogether. It formed a dense bundle of twigs, the sort that people might fashion into a broom.

Germans call it Hexenbesen: witches’ broom. As legend had it, witches used magic spells to conjure the brooms to fly across the night sky. The witches used some as nests, too, leaving them for hobgoblins to sleep in.

In the 19th century, plant breeders found that if they cut witches’ broom from one tree and grafted it to another, the broom would grow and produce seeds. Those seeds would sprout into witches’ broom as well.

Today you can see examples of witches’ broom on ordinary suburban lawns. Dwarf Alberta spruce is a landscaping favorite, growing up to ten feet high. It comes from northern Canada, where botanists in 1903 discovered the first known dwarf clinging to a white spruce — a species that can grow ten stories tall.

Pink grapefruits arose in much the same way. A Florida farmer noticed an odd branch on a Walters grapefruit tree. These normally bear white fruit, but this branch was weighed down with grapefruits that had pink flesh. Those seeds have produced pink grapefruit trees ever since.

Charles Darwin was fascinated by such oddities. He marveled at reports of “bud sports,” strange, atypical blooms on flowering plants. Darwin thought they held clues to the mysteries of heredity.

The cells of plants and animals, he reasoned, must contain “particles” that determined their color, shape and other traits. When they divided, the new cells must inherit those particles.

Something must scramble that heritable material when bud sports arose, Darwin declared, like “the spark which ignites a mass of combustible matter.”

Only in the 20th century did it become clear that this combustible matter was DNA. After one cell mutates, scientists found, all its descendants inherit that mutation.

Witches’ broom and bud sports eventually came to be known as mosaics, after the artworks made up of tiny tiles. Nature creates its mosaics from cells instead of tiles, in a rainbow of different genetic profiles.

Before DNA sequencing was commonplace, scientists struggled to tell the genetic differences between human cells. Cancer offered the first clear evidence that humans, like plants, could become mosaics.

In the late 1800s, biologists studying cancer cells noticed that many of them had oddly shaped chromosomes. A German researcher, Theodor Boveri, speculated at the turn of the century that gaining abnormal chromosomes could actually make a cell cancerous.

As soon as Boveri floated his theory, he faced intense opposition. “The skepticism with which my ideas were met when I discussed them with investigators who act as judges in this area induced me to abandon the project,” he later said.

Boveri died in 1915, and it took nearly five decades for scientists to discover he was right.

David A. Hungerford and Peter Nowell found that people with a form of cancer called chronic myelogenous leukemia were missing a substantial chunk of chromosome 22. It turned out a mutation had moved that chunk over to chromosome 9. The cells that inherited that mutation became cancerous.

It’s hard to think that a tumor might have anything in common with a pink grapefruit. Yet they are both products of the same process: lineages of cells that gain new mutations not found in the rest of the body.

Some skin diseases proved to be caused by mosaicism, too. Certain genetic mutations cause one side of the body to become entirely dark. Other mutations draw streaks across the skin.

The difference is in the timing. If a cell gains a mutation very early in development, it will produce many daughter cells that will end up spreading across much of the body. Late-arising mutations will have a more limited legacy.

A Brain Biography

Dr. Walsh and his colleagues have found evidence of mosaicism in some very unexpected places.

They investigated a mysterious disorder called hemimegalencephaly, which causes one side of the brain to become overgrown. The researchers examined tissue from patients who had brain surgery to treat the seizures triggered by hemimegalencephaly.

Some of the brain cells in the patients — but not all of the cells — shared the same mutant genes. It’s possible that these mutant neurons multiplied faster than others in the brain, triggering one side to become enlarged.

Preliminary studies suggest that mosaicism underlies many other diseases. Last year, Christopher Walsh, a geneticist at Harvard University, and his colleagues published evidence that mosaic mutations may raise the risk of autism.

But scientists are also finding that mosaicism does not automatically equal disease. In fact, it’s the norm.

When a fertilized egg — known as a zygote — starts dividing in the womb, many of its early descendant cells end up with the wrong number of chromosomes. Some are accidentally duplicated, and others lost.

Most of these unbalanced cells divide only slowly or die off altogether, while the normal cells multiply far faster. But a surprising number of embryos survive with some variety in their chromosomes.

Markus Grompe, a biologist at Oregon Health & Science University, and his colleagues looked at liver cells from children and adults without liver disease. Between a quarter and a half of the cells were aneuploids, typically missing one copy of one chromosome.

CreditJason Holley

Along with altered chromosomes, human embryos also gain smaller mutations in the genome. Stretches of DNA may be copied or deleted. Single genetic letters may get incorrectly reproduced.

It wasn’t possible to study such molecular changes accurately until DNA-sequencing technology became sophisticated enough.

In 2017, researchers at the Wellcome Trust Sanger Institute in England examined 241 women, sequencing batches of white blood cells from each. Every woman had acquired about 160 new mutations, each present in a sizable fraction of her cells.

The women gained these mutations as embryos, the scientists theorized, with two or three new mutations arising each time a cell divided. As those new mutations occurred, the embryonic cells passed them all down to their descendants, a mosaic legacy.

Dr. Walsh and his colleagues have discovered intricate mosaics in the brains of healthy people. In one study, they plucked neurons from the brain of a 17-year-old boy who had died in a car accident. They sequenced the DNA in each neuron and compared it to the DNA in cells from the boy’s liver, heart and lungs.

Every neuron, the researchers found, had hundreds of mutations not found in the other organs. But many of the mutations were shared only by some of the other neurons.

It occurred to Dr. Walsh that he could use the mutations to reconstruct the cell lineages — to learn how they had originated. The researchers used the patterns to draw a sort of genealogy, linking each neuron first to its close cousins and then its more distant relatives.

When they had finished, the scientists found that the cells belonged to five main lineages. The cells in each lineage all inherited the same distinctive mosaic signature.

Even stranger, the scientists found cells in the boy’s heart with the same signature of mutations found in some brain neurons. Other lineages included cells from other organs.

Based on these results, the researchers pieced together a biography of the boy’s brain.

When he was just an embryonic ball in the womb, five lineages of cells had emerged, each with a distinct set of mutations. Cells from those lineages migrated in different directions, eventually helping to produce different organs — including the brain.

The cells that became the brain turned into neurons, but they did not all belong to the same family. Different lineages merged together. In essence, the boy’s brain was made of millions of mosaic clusters, each composed of tiny cellular cousins.

It’s hard to say what these mosaic neurons mean to our lives — what it means for each of us to have witches’ broom growing in our skulls. “We don’t know yet whether they have any effect on shaping our abilities or challenges,” said Dr. Walsh.

What we do know is that mosaicism introduces randomness into the development of our brains. Mutations, which arise at random, will form different patterns in different people. “The same zygote would never develop exactly the same way twice,” said Dr. Walsh.

A Heart in Pieces

As ubiquitous as mosaicism may be, it’s still easy to overlook — and surprisingly hard to document.

Astrea Li, the infant examined by Dr. Priest at Stanford, had gone into cardiac arrest the day she was born. Her doctors put a defibrillator in her heart to shock it back into the proper rhythm.

Dr. Priest sequenced Astrea’s genome to search for the cause of her disorder. He concluded that she had a mutation in one copy of a gene called SCN5A. That mutation could have caused her trouble, because it encodes a protein that helps trigger heartbeats.

But when Dr. Priest ran a different test, he couldn’t find the mutation.

To get to the bottom of this mystery, he teamed up with Steven Quake, a Stanford biologist who had pioneered methods for sequencing the genomes of individual cells. Dr. Priest plucked 36 white blood cells from the child’s blood, and the scientists sequenced the entire genome of each cell.

In 33 of the cells, both copies of a gene called SCN5A were normal. But in the other three cells, the researchers found a mutation on one copy of the gene. Astrea had mosaic blood.

Her saliva and urine also turned out to contain mosaic cells, some of which carried the mutation. These findings demonstrated that Astrea had become a mosaic very early in her development.

The skin cells in her saliva, the bladder cells in her urine and her blood cells each originated from a different layer of cells in two-week-old embryos.

Astrea’s SCN5A mutation must have originated in a cell that existed before that stage. Its daughter cells later ended up in those three layers, and ultimately in tissues scattered throughout her body.

They might very well have ended up in her heart, too. And there the mutation could have theoretically caused Astrea’s problems.

While Dr. Priest was reconstructing Astrea’s mosaic origins, she was recovering from the surgery to implant her defibrillator. Her parents, Edison Li and Sici Tsoi, brought her home. And for a few months, it seemed she was out of the woods.

One day, however, her defibrillator sensed an irregular heartbeat and released a shock — along with a wireless message to Astrea’s doctors.

Back at the hospital, doctors discovered a new problem: her heart had become dangerously enlarged. Researchers have linked mutations in the SCN5A gene to the condition.

Her heart soon stopped. Her doctors attached a mechanical pump, and soon a donated heart became available.

Astrea underwent transplantation surgery and recovered well enough to go home. She went on to enjoy a normal childhood, performing cartwheels with her sister and listening obsessively to the soundtrack of “Frozen.”

The transplant did not just give Astrea a new lease on life. It also gave Dr. Priest a very rare chance to look at a mosaic heart up close.

The transplant surgeons had clipped some pieces of Astrea’s cardiac muscle. Dr. Priest and his colleagues extracted the SCN5A gene from the cells taken from different parts of her heart.

On the right side of the heart, he and his colleagues found that more than 5 percent of the cells had mutant genes. On the left, nearly 12 percent did.

To study the effect of this mosaicism, Dr. Priest and his colleagues built a computer simulation of Astrea’s heart. They programmed it with grains of mutant cells and let it beat.

The simulated heart thumped irregularly, in much the same way Astrea’s had.

The experience left Dr. Priest wondering how many more people might be at risk from a hidden mix of mutations.

Unless he winds up with another patient like Astrea, we may never find out.



This article was originally published in The New York Times.  Read the original article.

Cracking the Code of Life—at Light Speed

The biological code of mankind—three billion pairs of chemical “bases,” twisted clockwise into DNA’s iconic double-helix—was declared fully transcribed, at long last, 15 years ago. On April 14, 2003, the leaders of the Human Genome Project, an effort backed by the U.S. government, proclaimed their sequence “essentially complete.” Including the preliminary work, the task had taken 13 years and cost American taxpayers $2.7 billion.

These days, thanks to technical leaps that put Moore’s Law to shame, scientists are sequencing practically everything in sight. Consider the mystery posed by a geriatric bat. “Usually with animals,” says Mike Hunkapiller, “the bigger they are, the longer they live. There’s a bat that’s that big”—his thumb and forefinger curl into a circle about the size of a quarter—“that lives 50 years.” Studying the bat’s DNA to suss out its secret could someday, perhaps, prolong human life. “There’s all kinds of reasons why a lot of these animal models are not just for basic research,” he says. “They’re to understand what you learn from them about us.”

Mr. Hunkapiller, age 67, has been in the forefront of genomics for a long time. As a postdoc at Caltech in the 1980s, he helped invent the first automated DNA-sequencing machine. In the 1990s he led a company whose sequencers drove not just the public Human Genome Project but also its privately funded competitor. Today he is CEO of Pacific Biosciences, known as PacBio, which aims to bring heavy sequencing artillery to the lab-coated grunts in the scientific trenches.

As the price of reading DNA has plummeted, large-scale sequencing projects have geared up, pledging to get the genomes of 5,000 species of arthropods, or 10,000 kinds of birds, or one of every vertebrate on Earth. For three years running, PacBio has held a public contest to find the “World’s Most Interesting Genome,” which is then sequenced on the company’s dime. Last year’s winner, a feral Australian dog called the desert dingo, defeated a Malaysian pit viper, a “solar powered” sea slug, and the bombardier beetle, which squirts its enemies with a caustic, boiling-hot liquid.

Cracking the Code of Life—at Light Speed

“There’s a program in China, from one of our customers, doing 100 ants,” Mr. Hunkapiller says. “We talked about that at one of our quarterly conference calls, and people were saying, ‘Well, who cares about 100 ants?’ ” In answer, he cites two groups that care a lot: farmers in Australia, losing millions of dollars in crops, and residents of the American South, trying to extinguish infestations of fire ants. Comparing the genomes of 100 ants may reveal differences that humans can exploit. The same holds true for other pests, such as the mosquitoes that spread the Zika virus. “You want to know,” Mr. Hunkapiller says, “what targets can I go after to kill that thing and control it, without causing damage to other organisms.”

PacBio’s latest model of sequencer is about the size and shape of a standard kitchen refrigerator, albeit a $350,000 one. To imagine how the machine works, start with a hole about 1/1,000th the width of a human hair. At the bottom is an enzyme that in nature helps copy DNA. Here it does the same job, but in a way that allows researchers to eavesdrop. The enzyme is fed a loop of DNA to duplicate, along with free-floating bases—the A’s, C’s, G’s and T’s that make up the genetic code—to use as raw material. Unlike in nature, however, the four flavors of bases have each been tagged with a different-colored fluorescent dye.

Now the real trick: A laser is aimed at the hole, but the beam’s wavelength makes it too big to fit through. If this idea seems strange, think of the protective window-grate on your microwave oven. The principle is the same: The microwaves are too wide to escape, which is why the oven nukes that sad Lean Cuisine and not your hungry face.

In the PacBio machine, the laser light peeks into the hole just enough to put a spotlight on that industrious little enzyme. Whenever the enzyme grabs a fluorescent base and incorporates it into the DNA strand, it glows with color. The machine records the light, blinking two or three times a second, and converts that data into the DNA sequence.

Serious bandwidth comes from putting the process into massive parallel: A PacBio chip 1.25 inches square has one million holes, flashing with light. The next version, due out in 2019, is expected to have eight million holes. At that point, the company says its cost in supplies and chemicals to create a finished human genome, from scratch, should drop from roughly $15,000 to something like $1,500.

But the big competitive advantage touted by PacBio is that its machine spits out long DNA sequences. The average read has climbed to 15,000 base pairs, with some pushing up toward 100,000 before the enzyme peters out. For comparison, during the Human Genome Project, the average fragment was on the order of 500 base pairs.

That difference matters particularly when assembling a full genome for the first time, without the aid of a reference. To put the length of the human genome in perspective, if a cell’s DNA were unraveled from its 23 pairs of chromosomes, it would stretch about 6 feet. Once it’s blasted at random into minuscule segments that are then sequenced, a computer has to figure out, piece by piece, how to fit them together again.

An analogy would be to try reconstructing “War and Peace” from a couple of dozen shredded books. Yet the chore is far more tedious even than that, since the human genome reads, for three billion letters, like this: “atgtctggctctgttccccagactggagtgcggcgac . . .” The supercomputer that assembled one of the initial human sequences examined 26 million fragments and made 500 quintillion—that’s 500 million trillion—base-to-base comparisons.

Having puzzle pieces now that are 30 times as big certainly helps. In addition, reading longer fragments allows scientists to tackle very repetitive genomes that otherwise would be difficult to assemble. The sequence for bread wheat, at 15 billion base pairs, was finished last year.

Then in January researchers reported they had cracked the biggest genome yet, the 32 billion pairs belonging to the axolotl, also called the Mexican salamander. Mr. Hunkapiller says there’s no grand theory to explain why some genomes are so much longer than others, but in amphibians the repetition may contribute to their ability to regenerate. “An axolotl is a classic example: You can cut a leg off and it grows back. You can’t do that with your leg, right?” he says. “They tend to have redundancy in their genome, and there’s some thought that that has something to do with the ability to do that.”

The same difficulty of highly repetitive DNA also exists in parts of the human genome. That’s why the 2003 announcement of its “effective completion” mentioned about 400 gaps “that cannot be reliably sequenced with current technology.” Some of these have since been filled; the official human reference sequence is up to “build 38.” Still, blank spots remain at the ends of chromosomes (called telomeres), as well as at the axis points where the two arms of a chromosome meet (called centromeres). Could those uncharted areas have hidden functions, particularly ones that implicate disease? At this stage, we just don’t know, Mr. Hunkapiller says. “Those repeats are not all identical. There are variations,” he says. “They’re clearly important. I mean, telomeres are involved in cellular aging. You can only go through so many generations of most cells because of that.”

When the human genome was first decoded, the hopes for a quick medical payoff were high. One prediction was that by 2010 every newborn baby would come home from the hospital with its DNA sequence on a DVD. Mr. Hunkapiller blames the hype on competitive jockeying as two teams raced to finish the human sequence first.

The government-funded effort, led by Francis Collins (now director of the National Institutes of Health), originally planned to complete its work by 2005. But then in 1998 Mr. Hunkapiller’s parent company, impressed by the speed of his new sequencers, decided to take on the job itself. The result was a new firm called Celera, led by J. Craig Venter. It planned to beat the government operation by four full years—and to release its data in tranches only after giving its paying subscribers, like pharmaceutical companies, a good look.

Soon the two sides were trading barbs. Mr. Collins said the Celera genome would be “the CliffsNotes or the Mad Magazine version.” Mr. Venter said the public project was “putting good money after bad.” In the end, the two men agreed to—or were forced into—a truce. At a White House ceremony in 2000, hosted by Bill Clinton and Tony Blair, they appeared jointly to announce that drafts of both sequences had been completed. Mr. Hunkapiller, though invited, was stuck at home with chickenpox.

An advantage of the public-private race was that it hurried along the sequencing. A disadvantage, in Mr. Hunkapiller’s telling, was the escalating salesmanship. “Saying that you’d learn enough about the genome to cure all diseases was nuts,” he says. Did the hyperbole really get that far? “Oh, yeah, Craig was pretty close—and so was Francis Collins, to be fair.”

Fifteen years later there’s a lot of medicine yet to be wrung out of genomics. A startling fact is that when a patient is suspected of having an unknown genetic illness, the “solve rate” is 50% or less. Mr. Hunkapiller says PacBio’s machines can help by detecting what are called “structural variants,” changes to DNA that may involve hundreds or even thousands of base pairs, making them difficult to pick up with earlier technology. Last year a group at Stanford was able to diagnose a young man whose heart had repeatedly grown benign tumors. One of his genes on Chromosome 17 was missing 2,200 base pairs.

For multifactor diseases, it appears to be a matter of drawing signal from the noise. Two years ago it was front-page news when researchers found a gene variant that significantly increased a person’s risk of schizophrenia—from 1% to 1.25%, an absolute change too small to be very meaningful. “In the case of genetic diversity, because there’s so much of it, you need statistical power, which is large numbers of samples,” Mr. Hunkapiller says. “But you have to know how to sort things out so that you’re not comparing apples to oranges to pears to axolotl.” The NIH will soon launch a program to sequence DNA from one million people living in the U.S., and Mr. Hunkapiller thinks that data could help, provided it includes decent patient histories and other ancillary material.

Cancer is another opportunity for sequencing, given how scrambled its DNA can be. “If you look at a cancer cell line, you wonder: How is this thing alive?” Mr. Hunkapiller says, “Because you have so much jumbling of bits of chromosomes here and there, and big chunks lost, and big chunks—you’ve got dozens of copies of that region.” Some cancer variants can be targeted by specific drugs, and Mr. Hunkapiller says others can help appraise prognosis. “Is this going to be a really bad prostate cancer, or is it going to be relatively benign?” he says. “More and more, sequencing is being done to figure that out.”

An area of research to watch, Mr. Hunkapiller says, is the idea of using blood tests to detect cancer early by spotting infinitesimal amounts of DNA released when tumor cells die. “It’s not going to be trivial to do that, just because you’re looking at a tiny needle in a big haystack,” he says. “But there’s probably cases where that’s going to help, because there are some cancers that are just—you never find them early enough. The symptoms aren’t there and you can’t really go in and biopsy. Pancreatic cancer is an example of that. By the time you find out about it, unless it’s a particular type, you’re in trouble.”

And as for those newborn babies? Mr. Hunkapiller’s freshest grandson, 3-month-old Asher, received elective genetic testing for 193 different conditions. “Yeah, well, you’ve got two molecular biologists as parents in that case,” he says with a laugh. “Fortunately, they didn’t learn anything that they were scared of from that.” Scanning a couple of hundred genes, granted, isn’t quite the promised sequence on a DVD. But eventually, Mr. Hunkapiller insists, new moms and dads who want the whole 9 yards—or, rather, the whole 2 yards and three billion letters—will have that option, too. “I wouldn’t say it’s going to be in the next two years,” he says. “Twenty? Probably.”



This article was originally published in The Wall Street Journal. Read the original article.

Police have used genealogy to make an arrest in a murder case

ON APRIL 24th police in California announced the arrest of Joseph DeAngelo. Mr DeAngelo stands accused of eight counts of murder. On April 27th some intriguing details emerged of what had prompted the arrest. The starting-point was genetic material recovered from the crime scenes. Though this directly matched no DNA held in a police database, analysis of it led investigators all the way back to the 1800s, to Mr DeAngelo’s great-great-great grandparents. The trail they followed allegedly links Mr DeAngelo to crimes committed around Sacramento in the 1970s and 1980s by an unknown man who acquired the nickname of the Golden State Killer, and who murdered at least 12 people and raped more than 50.

That a link to distant ancestors could lead to an arrest is testament to the power of modern genomics. Investigators first uploaded Mr DeAngelo’s genetic profile to a website called GEDmatch. This allows anyone to use his or her own genetic profile to search for family connections. GEDmatch’s database turned out to hold profiles, returned as weak matches, which looked as if they had come from distant cousins of the Golden State Killer. GEDmatch encourages uploaders to include their real name with their genomes, and the investigators were able to trace back through the matches’ parents and grandparents to find their most recent common ancestor. Then, having moved backward in time, they moved forward again, looking for as many as possible of this ancestor’s descendants. Using newspaper clippings, census records and genealogy websites, they discovered some 25 family trees stretching down from the common ancestor. On its own, the tree on which Mr DeAngelo appears has 1,000 members.

After that, old-fashioned sleuthing took over. From these thousands of descendants, the detectives found two who had had connections with Sacramento at the time the Golden State Killings were taking place. One was eliminated from the investigation by further DNA tests of a family member. The other, Mr DeAngelo, was arrested after police had tested the DNA on an item he had discarded.

Serial privacy

If a serial killer really has been caught using these methods, everyone will rightly applaud. But the power of forensic genomics that this case displays poses concerns for those going about their lawful business, too. It bears on the question of genetic privacy—namely, how much right people have to keep their genes to themselves—by showing that no man or woman is a genetic island. Information about one individual can reveal information about others—and not just who is related to whom.

With decreasing degrees of certainty, according to the degree of consanguinity, it can divulge a relative’s susceptibilities to certain diseases, for example, or information about paternity, that the relative in question might or might not want to know, and might or might not want to become public. Who should be allowed to see such information, and who might have a right to see it, are questions that need asking.

They are beginning to be asked. In 2017 the Court of Appeal in England ruled that doctors treating people with Huntington’s chorea, an inherited fatal disease of the central nervous system the definitive diagnosis of which is a particular abnormal DNA sequence, have a duty to disclose that diagnosis to the patient’s children. The children of a parent who has Huntington’s have a 50% chance of inheriting the illness. In this case, a father had declined to disclose his newly diagnosed disease to his pregnant daughter. She was, herself, subsequently diagnosed with Huntington’s. She then sued the hospital, on the basis that it was her right to know of her risk. Had she known, she told the court, she would have terminated her pregnancy.

That is an extreme case. But intermediate ones exist. For example, certain variants of a gene called BRCA are associated with breast cancer. None, though, is 100% predictive. If someone discovers that he or she is carrying such a variant, should that bring an obligation to inform relatives, so that they, too, may be tested? Or does that risk spreading panic to no good end?

It may turn out that such worries are transient. As the cost of genetic sequencing falls, the tendency of people to discover their own genetic information, rather than learning about it second-hand, will increase. That, though, may bring about a different problem, of genetic snooping, in which people obtain the sequences of others without their consent, from things like discarded coffee cups. At that point genetic privacy really will be a thing of the past.



This article was originally published in The Economist. Read the original article.

The ramifications of a new type of gene

WHAT’S a gene? You might think biologists had worked that one out by now. But the question is more slippery than may at first appear. The conventional answer is something like, “a piece of DNA that encodes the structure of a particular protein”. Proteins so created run the body. Genes, meanwhile, are passed on in sperm and eggs to carry the whole process to the next generation.

None of this is false. But it is now clear that reality is more complex. Many genes, it transpires, do not encode proteins. Instead, they regulate which proteins are produced. These newly discovered genes are sources of small pieces of RNA, known as micro-RNAs. RNA is a molecule allied to DNA, and is produced when DNA is read by an enzyme called RNA polymerase. If the DNA is a protein-coding gene, the resulting RNA acts as a messenger, taking the protein’s plan to a place where proteins are made. Micro-RNAs regulate this process by binding to the messenger RNA, making it inactive. More micro-RNA means less of the protein in question, and vice versa.

Often, this regulation is in response to environmental stimuli such as stress. And sometimes, the responses acquired in this way seem to be passed down through the generations, in apparent defiance of conventional genetic theory. The best known example in people comes from the Netherlands, which suffered famine in 1944, at the end of the second world war. Children born of starved mothers were, as might be expected, smaller than usual. But the children of those children were also small. Experiments carried out on mice confirm these observations.

Stress city

In the case of mothers, it is now believed that this process, called intergenerational epigenesis, is caused by micro-RNAs from the parent getting into eggs as they form in a developing fetus. That makes sense. Eggs are large cells, with room to accommodate these extra molecules. But intergenerational epigenetic effects can pass down the male line as well. And how paternal micro-RNAs come to be in an egg is a mystery, for the sperm that would have to carry them there are tiny and have no spare room. Work by Jennifer Chan, a graduate student at the University of Pennsylvania, has, however, shed light on the process.

Ms Chan’s solution was described on February 16th by her research supervisor, Tracy Bale of the University of Maryland, at the annual meeting of the American Association for the Advancement of Science (AAAS), in Austin, Texas. The crucial insight behind her study was that micro-RNAs need not actually get inside sperm cells as they form. They could equally well be attached to sperm just before sexual intercourse. Ms Chan therefore concentrated her attentions on part of the male genital tract called the epididymis. This is where sperm mature. Cells lining the epididymis constantly discharge small, fluid-filled, membrane-bound bubbles called vesicles. When Ms Chan, working with mice, looked in detail at these vesicles, she found that they contained lots of micro-RNAs.

That was interesting. But she then went on to do an experiment. Mice are easily stressed. Simply putting new objects into their living space is enough to induce significant changes in their levels of stress hormones. Stress a male in this way and his offspring (of either sex) will react less to stress than do the offspring of unstressed males. That looks like intergenerational epigenesis. It also makes evolutionary sense, since it calibrates a mouse’s stress response to the stressfulness of the environment—which is likely to be the same as that of its father. To prove that this intergenerational effect was caused by epididymal micro-RNAs, Ms Chan collected these molecules and injected them into fertilised mouse eggs. Those eggs, as she had hypothesised they would, grew into less-stress-reactive adults.

This work is all in mice. But Dr Bale has now roped some men into the experiment, too—namely 25 male students who have provided regular semen samples in order that the micro-RNAs therein can be tracked and correlated with such stressful events as sitting exams. The results of this are yet to come in. But, with her mouse work alone, it looks as if Ms Chan has cracked an important part of the puzzle of intergenerational epigenesis.

Response to stress is not, however, the only thing in which micro-RNAs are implicated. They are also suspected of involvement in schizophrenia and bipolar disorder. To investigate this, a second speaker at the AAAS meeting, Paul Kenny, of the Icahn School of Medicine, in New York, also turned to mice.

The root of Dr Kenny’s suspicion was the discovery, post mortem, in the brains of patients who had been suffering from these conditions, of elevated levels of three micro-RNAs, called MiR206, MiR132 and MiR133b. He and his colleague Molly Heyer therefore looked at the role of these micro-RNAs in regulating brain cells called parvalbumin interneurons, which are thought to be involved in schizophrenia.

Picking one, MiR206, for closer examination, the two researchers created a mouse strain in which the gene for MiR206 was switched off in the parvalbumin interneurons. They then performed experiments to study the behaviour of these mice, assuming that switching the gene off might protect them against schizophrenia-like symptoms. Surprisingly, they found the opposite.

Their first experiment was to play the mice a sudden, loud noise. This will startle any creature, mouse or man. If the noise is preceded by a softer one, however, both humans and murines react far less when the loud noise comes. They are expecting it. But people with schizophrenia seem never to learn this expectation. And neither, to the researchers’ surprise, do mice with the MiR206 knockout.

The scary moment

For people, these observations are often explained by the fact that one symptom of schizophrenia is increased fear. And, in a second experiment, Dr Kenny and Dr Heyer showed, again contrary to expectation, that MiR206-knockouts were unusually fearful as well.

The researchers used a box which contained two lights, each positioned above a lever. First, a light would blink on and go off. Then, after a delay, both lights would come on. That was the signal for the mouse to press a lever. If the lever the mouse pressed was the one not under the initial light, the animal received some food. Drs Kenny and Heyer found that the knocked-out mice collected less food than did normal ones. But this was not because they were making mistakes. If they pressed a lever, they picked the correct one as often as a normal mouse would. Instead, they were pressing any lever less often. That was because they spent most of their time hiding in the corners of the box opposite the wall with the lights and levers. Again, they seemed abnormally afraid.

What all this means for the study of schizophrenia is unclear. It is possible that examination of the other two pertinent micro-RNAs may shed more light on the matter. More generally, though, both Dr Kenny’s work and Ms Chan’s are good examples of the fact that there is more to genes than was once believed.



This article was originally published in The Economist. Read the original article.

The Struggle to Build a Massive ‘Biobank’ of Patient Data

This spring, the National Institutes of Health will start recruiting participants for one of the most ambitious medical projects ever envisioned.

The goal is to find one million people in the United States, from all walks of life and all racial and ethnic groups, who are willing to have their genomes sequenced, and to provide their medical records and regular blood samples.

They may choose to wear devices that continuously monitor physical activity, perhaps even devices not yet developed that will track heart rate and blood pressure. They will fill out surveys about what they eat and how much.

If all goes well, experts say, the result will be a trove of health information like nothing the world has seen. The project, called the All of Us Research Program, should provide new insights into who gets sick and why, and how to prevent and treat chronic diseases.

The All of Us program joins a wave of similar efforts to construct gigantic “biobanks” by, among others, the Department of Veterans Affairs, a British collaboration and private companies like Geisinger Health Systems and Kaiser Permanente.

But All of Us is the only one that attempts to capture a huge sample that is representative of the United States population. “It will be transformative,” said Dr. Francis Collins, director of the National Institutes of Health.

It will also be expensive.

In 2017 alone, the budget for All of Us was $230 million, of which $40 million came from the 21st Century Cures Act. Congress has authorized an astounding $1.455 billion over 10 years for the project.

While supporters say the results will be well worth the money and effort, others have begun to question whether All of Us is just too ambitious, too loaded with cumbersome bureaucracy — and too duplicative of smaller programs that are moving much more quickly.

In the three years since the All of Us program was announced, not a single person’s DNA has been sequenced. Instead, project leaders have signed up more than 17,000 volunteers as “beta testers” in a pilot phase of the program. They supplied blood and urine samples, had measurements taken, and filled out surveys.

Dr. George D. Yancopoulos, the president and chief scientific officer of the biotech company Regeneron, said the N.I.H. did not have much to show for three years of planning. Regeneron has been deeply involved in similar public and private efforts, sequencing the DNA of more than 300,000 participants.

The beta testers constitute just 1.7 percent of the program’s target, Dr. Yancopoulos noted, and the investigators have collected only the simplest data, not genetic sequences.

“At this rate, when will they complete their one million-person target?” he wondered. “And at what taxpayer cost?”

“I think someone needs to ask tough questions about whether this is the best use of precious N.I.H. resources,” he added. “Should the funding instead go to individual researchers who are doing truly basic and innovative science?”

Two large health providers — Geisinger and Kaiser Permanente — both backed away from grants to participate in All of Us.

David Ledbetter, executive vice president and chief scientific officer of Geisinger, said that the program’s complexity made it too time-consuming: conference calls upon conference calls, meetings upon meetings, without much progress.

“We decided it was not the right expenditure of our time,” he said. Geisinger gave back its award that was potentially worth $50 million over five years.


Dr. Francis Collins, director of the National Institutes of Health, testifying before the Senate in 2010. All of Us “will be transformative,” he said. CreditChip Somodevilla/Getty Images

Geisinger has enrolled more than 180,000 participants in a biobank of its own, and the health system already has years of their medical records. Regeneron is sequencing the participants’ DNA and has completed more than 100,000.

Dr. Ledbetter said the N.I.H. program would be “very valuable someday.” But Geisinger, he said, did not want to wait.

“Someday is today,” he said.

Kaiser Permanente, too, is now far ahead in developing its own biobank. Originally, the company expected that the federal project would profit from Kaiser’s experience with recruiting and data analysis, said Elizabeth McGlynn, vice president of Kaiser Permanente Research.

“We were not able to engage as a scientific partner,” Dr. McGlynn said. “We felt increasingly that we were just being asked to give access to our members.”

DeCode Genetics, a subsidiary of Amgen, a biotech company, is working with a biobank of 160,000 people from Iceland. Dr. Sean E. Harper, Amgen’s executive vice president for research and development, says it is hard to imagine the complexity of analyzing the data.

“It took about 20 years and over a billion dollars of investment to get to the point where we are able to routinely extract from the data the necessary information to validate or invalidate drug targets,” he said. Sequencing the DNA is the easy part, he said. “The hard part is to get all these medical records and lab tests curated in a computer system where they are query-able and to perfect the analytics.”

Despite these concerns, All of Us has contracted with scientists at just about every leading university, as well as with companies like Verily, a subsidiary of Alphabet, parent company of Google.

“We will have an unprecedented amount of data at a scale never done before,” said Eric Dishman, director of the program.

Investigators have grand plans for all that data once it becomes available.

Dr. Atul Butte, director of the Institute for Computational Health Sciences at the University of California, San Francisco, hopes to find the earliest signs of disease, especially of Type 2 diabetes.

“Do you go back and forth from diabetes for a while?” he asks. “Is it preventable?”

The Veterans Affairs Department began building a similar biobank, called the Million Veteran Program, in 2011 with a very lean budget: just $250 million over the past seven years.

The agency has recruited 650,000 vets so far and has years of their medical records, including prescription data. Investigators expect to sequence the DNA of 100,000 participants in the next two years, at a cost of $70 for each person’s entire genome. The data will be public.

The British program, called the U.K. Biobank, has half a million participants with complete medical records and additional data for some, including body and brain scans.

Regeneron has committed to sequencing the DNA of all of the participants by the end of 2019. After a six to 12 month period of exclusivity, the company will make that data public.

But what All of Us is attempting to do is much more complex, said Dr. Dishman. The U.K. project and the program at Geisinger lack a representative range of racial and ethnic groups; the V.A.’s biobank has relatively few women.

All of Us will be built to reflect the United States population. The San Francisco General Hospital Foundation, for instance, was given a grant to recruit lesbian, bisexual, gay and transgender participants.

“I think what the U.S. project adds is that it reflects the diversity of the U.S.,” said Dr. Sekar Kathiresan, a geneticist at the Broad Institute and an investigator with the N.I.H. program.

That’s partly why planning for the project has dragged on. And the diversity of participants makes the daunting task of retrieving medical records even more difficult.


President Obama signing the 21st Century Cures Act into law in 2016. The act authorized $1.455 billion for the All of Us program over 10 years. CreditAl Drago/The New York Times

Americans tend to have medical records stored slapdash all over the place, and they change insurers and medical plans frequently. There is little uniformity in the country’s electronic health systems.

Even the most straightforward part of the project — DNA sequencing — is formidable.

“There are not enough sequencing machines in the U.S. to just focus on our project,” Dr. Dishman acknowledged. All of Us will depend on prices falling for sequencing — and more sequencers being built.

For participants, there will be a reward, Dr. Collins noted. The program will give them genetic information and health data, and tell them how they compare to others in the population.

To do that, All of Us plans to enlist genetic counselors. Yet right now, there are not nearly enough counselors to handle the task.

The counseling issue also bothered Kaiser, Dr. McGlynn said, and it was a factor in the decision to return the grant money.

“Genetic counselors are in terribly short supply,” she said. “We wanted to be sure we were well organized to deliver results in a way that was ethical and not scary to members.”

The accumulation of tremendous caches of medical data is raising troubling questions about what participants should be told. The U.K. Biobank, for instance, considered returning results to participants, but decided against it after an experiment.

It involved participants getting whole body scans for the program. For some subjects, a radiologist systematically assessed the scans to see if anything seemed abnormal. If it did, the patient and the patient’s doctor were informed.

As it turned out, 20 percent of the participants had abnormalities. They often went on to have other tests, some of which were invasive and involved major surgery, like removal of a lobe of the lung.

Yet in the end, only one in eight with abnormal scans actually had a medical problem, and even then there was nothing they could do about it most of the time, said Dr. Rory Collins, chief executive of the U.K. project.

“What we are trying to do is not provide care to individuals, but to generate a resource that can provide health information,” Dr. Collins said. “Feedback can cause more harm than good.”

Other experts disagree with the British approach. At Geisinger, participants are told if they have a genetic variant that might affect their disease risk.

They are offered genetic counseling if they want it — and so far, about two-thirds do. The medical system has sufficient counselors to handle the demand, said Adam H. Buchanan, co-director of the counseling program.

Given the substantial obstacles, will the N.I.H. project, which has not even really begun, be worth the immense expense and effort?

Dr. Collins, an adviser to All of Us, thinks it will. Huge amounts of data will be needed to really understand interactions between genetics, environment and lifestyle.

“Half a million people isn’t enough. Even a million isn’t enough,” he said.

Dr. Ledbetter was more circumspect. “I think the idea is great,” he said. “It is ambitious. It is expensive. It will take a while.”

“I wish the N.I.H. well.”

Powerful enzyme could make CRISPR gene-editing more versatile

An enzyme modified in the laboratory could boost the utility of CRISPR–Cas9 gene editing by allowing researchers to tinker with more sites in the genome — while also reducing the risk of undesired changes.

These features could make the enzyme, called xCas9, a laboratory staple, says David Liu, a chemical biologist at the Broad Institute of Harvard and MIT in Cambridge, Massachusetts, who led the work. But it will need more testing before its full potential becomes clear, he adds. The study is published today in Nature1.

Since its introduction about five years ago, CRISPR–Cas9 gene editing has become a key tool in many biology laboratories around the world. The technique allows researchers to make changes to the genome at specific sites with much greater ease than previous methods, but it still has some frustrating limitations.

One is the need to have a specific DNA sequence, called a PAM sequence, next to the site to be modified. Different Cas9 enzymes found in nature require different PAM sequences. The Cas9 most commonly used in laboratories was isolated from the bacterium Streptococcus pyogenes, and its PAM allows researchers to target about one out of every sixteen sites in a genome.

That’s good enough for many applications: researchers who want to disable a gene, for example, can select many sites within that gene to edit. But PAMs can become restrictive when researchers are trying to make very specific changes, says biochemist Albert Jeltsch of the University of Stuttgart in Germany.

This could include researchers who are studying how particular DNA sequences, or chemical modifications to specific DNA letters, affect gene expression. “Relief from the PAM restriction is quite important,” says Jeltsch. “Some of these elements are quite small, and then the restriction can be quite relevant.”

Sharpening molecular scissors

To find a way around this, Liu and his colleagues harnessed a method that forced Cas9 to evolve rapidly in the laboratory, accumulating mutations that allowed it to cut next to a variety of PAM sites. Eventually, they ended up with xCas9, which can cut DNA at sites near a broad range of PAM sites and could target one-quarter of sites in a genome.

The team tested its enzyme on dozens of sites in the genome, and combined it with tools called base editors to allow it to swap one DNA letter for another. To Liu’s surprise, xCas9 was also less likely to cut at other sites in the genome than the standard laboratory enzyme.

The same approach could be used to alter other variants of the Cas9 enzyme, including the relatively small Cas9 proteins that some hope to use for gene therapy, says bioengineer Prashant Mali of the University of California, San Diego. Those proteins, he says, tend to have frustratingly restrictive PAM sequences.

Synthetic biologist Stanley Qi of Stanford University in California calls the work “dazzling”, and says his team is eager to try it in the laboratory. “I am amazed that the new Cas9 has both broader PAM recognition and higher specificity,” he says. “That’s amazing biology.”




This article was originally published in Nature. Read the original article.

Genome editor CRISPR’s latest trick? Offering a sharper snapshot of activity inside the cell

Airplane flight recorders and body cameras help investigators make sense of complicated events. Biologists studying cells have tried to build their own data recorders, for example by linking the activity of a gene of interest to one making a fluorescent protein. Their goal is to clarify processes such as the emergence of cancer, aging, environmental impacts, and embryonic development. A new cellular recorder that borrows from CRISPR, the revolutionary genome editing tool, now offers what could be a better taping device that captures data on DNA.

In Science online this week, chemist David Liu and postdoc Weixin Tang, both of Harvard University, unveil two forms of what they call a CRISPR-mediated analog multievent recording apparatus, or CAMERA. In proof-of-concept experiments, they show in both bacterial and human cells how this tool can record exposure to light, antibiotics, and viral infection or document internal molecular events. “The study highlights the really creative ways people are harnessing discoveries in CRISPR to build these synthetic pathways,” says Dave Savage, a protein engineer at the University of California, Berkeley.

Other investigators have created recording devices with CRISPR components, among them Timothy Lu of the Massachusetts Institute of Technology in Cambridge. But Lu notes that his system was limited to bacteria, and compared with CAMERA it required “an order of magnitude” more cells to reliably record signals and had a much poorer signal-to-noise ratio. The new work, he says, “is really beautiful stuff” and has “a level of efficiency and precision that goes beyond what we did earlier.” (Lu this week plans to release a preprint describing a system similar to one version of CAMERA.)

The original use of CRISPR was to target and cut double-stranded DNA. Cells naturally repair these cuts, but in the process, they can introduce random, or stochastic, errors to a target gene, disabling it. Several groups have used these random errors as markers—or barcodes—to track how cells “differentiate” from one state to another.

A new lens on cells

One form of a research tool called CAMERA engineers cells to record signals triggered by various stimuli using the DNA of a “safe harbor” gene.

The gRNA shuttles the base editor to the target on the safe harbor gene.A cell’s response to a stimulus leads plasmids to produce guide RNA (gRNA) and a base editor.Base editor alters DNA, recording cell’s response to stimulus.StimulusgRNACytidine deaminaseCas9 nickaseGGCCTACellgRNABase editorBase editorAGTCTA


Liu sought a cleaner readout. “We wanted to shy away from that stochastic mixture. It’s much harder to interpret your findings.” His team also aimed to record not just whether a cell experienced a stimulus, but how strong it was and how long it lasted. To better understand cancer, for example, Liu says, “We’d love to be able to see whether cells in certain states listen to or ignore signals to stop growing.”

One form of CAMERA takes advantage of a peculiarity of bacteria: the circular “plasmids” of DNA that float in their cytoplasm, copying themselves but tightly regulating their population size. The researchers introduced two “recorder” plasmids, R1 and R2, that settle at a stable ratio. They then fashioned a separate plasmid with genes for CRISPR’s components—a “guide” RNA (gRNA) that targets a DNA sequence and the Cas9 enzyme that cuts the double helix. Those genes are designed to kick into action, making the components that target R1 for destruction, when the cell experiences a specific stimulus. In one test, they equipped bacteria with an antibiotic-activated CAMERA. By sequencing the plasmids and documenting how the R1:R2 ratio had changed, they could tell how long the cells had been exposed to the drug.

A second CAMERA makes use of a modified Cas9 that doesn’t cut the double helix and is linked to an enzyme that chemically switches cytosine, one of four DNA bases, into another one, thymine. To record an event, the gRNA shuttles this so-called base editor to a “safe harbor” gene, whose DNA can be altered without harming the cell. Again, the researchers tailor the system to respond to specific signals. As a test, they stimulated human cells to activate the Wnt signaling pathway, which plays a role in the development of embryos and in cancer. CAMERA turned on in the presence of Wnt activity, inscribing a record of those signals in the safe harbor gene.​

CAMERA works in samples that contain as few as 10 cells, nearing the goal of recording the actions of a single cell. “If you’re doing the activity map of the brain, each cell is a different story,” notes Harvard geneticist George Church, whose own lab has developed CRISPR-based recording devices. “Ideally you’d have a nice single molecule ticker tape recording of a DNA sequence that you could read off and it tells you what was happening in each cell over the function of time.”

CAMERA has other potentially useful features, including the ability to erase its recorded information, with drugs that “reset” the plasmid ratio to their baseline, for example. CAMERA also can record several different signals at the same time or one after the other. But for CAMERA to prove its worth in the crowded biological recording field, researchers have to show that it can work when engineered into the cells of an animal—not simply in the cell line used in Liu’s Wnt experiment. “The real power is what’s going to happen next,” Savage says. “Right now, the killer app is still to come.”



This article was originally published in Science. Read the original article.

Breaking the Seal on Drug Research

PETER DOSHI walked across the campus of Johns Hopkins University in a rumpled polo shirt and stonewashed jeans, a backpack slung over one shoulder. An unremarkable presence on a campus filled with backpack-toters, he is 32, and not sure where he’ll be working come August, when his postdoctoral fellowship ends. And yet, even without a medical degree, he is one of the most influential voices in medical research today.

Dr. Doshi’s renown comes not from solving the puzzles of cancer or discovering the next blockbuster drug, but from pushing the world’s biggest pharmaceutical companies to open their records to outsiders in an effort to better understand the benefits and potential harms of the drugs that billions of people take every day. Together with a band of far-flung researchers and activists, he is trying to unearth data from clinical trials — complex studies that last for years and often involve thousands of patients across many countries — and make it public.

The current system, the activists say, is one in which the meager details of clinical trials published in medical journals, often by authors with financial ties to the companies whose drugs they are writing about, is insufficient to the point of being misleading.

There is an underdog feel to this fight, with postdocs and academics flinging stones at well-fortified corporations. But they are making headway. Last fall, after prodding by Dr. Doshi and others, the drug giant GlaxoSmithKline announced that it would share detailed data from all global clinical trials conducted since 2007, a pledge it later expanded to all products dating to 2000. Though that data has not yet been produced, it would amount to more than 1,000 clinical trials involving more than 90 drugs, a remarkable first for a major drug maker.

The European Medicines Agency, which oversees drug approvals for the European Union, is considering a policy to make trial data public whenever a drug is approved. And on June 17, the medical world saw how valuable such transparency could be, as outside researchers published a review of a spinal treatment from the device maker Medtronic. The review, which concluded that the treatment was no better than an older one, relied on detailed data the company provided to the researchers.

Continue reading the main story

For years, researchers have talked about the problem of publication bias, or selectively publishing results of trials. Concern about such bias gathered force in the 1990s and early 2000s, when researchers documented how, time and again, positive results were published while negative ones were not. Taken together, studieshave shown that results of only about half of clinical trials make their way into medical journals.

Problems with data about high-profile drugs have led to scandals over the past decade, like one involving contentions that the number of heart attacks was underreported in research about the painkiller Vioxx. Another involved accusations of misleading data about links between the antidepressant Paxil and the risk of suicide among teenagers.

To those who have followed this issue for years, the moves toward openness are unfolding with surprising speed.

“This problem has been very well documented for at least three decades now in medicine, with no substantive fix,” said Dr. Ben Goldacre, a British author and an ally of Dr. Doshi. “Things have changed almost unimaginably fast over the past six months.”

Much of that change is happening because of what Dr. Goldacre calls an “accident of history.” In 2009, Dr. Doshi and his colleagues set out to answer a simple question about the anti-flu drug Tamiflu: Does it work? Resolving that question has been far harder than they ever envisioned, and, four years later, there is still no definitive answer. But the quest to determine Tamiflu’s efficacy transformed Dr. Doshi and others into activists for transparency — and turned the tables on drug makers. Until recently, the idea that companies should routinely hand over detailed data about their clinical trials might have sounded far-fetched. Now, the onus is on the industry to explain why it shouldn’t.

IN summer 2009, Dr. Doshi received a call from Dr. Tom Jefferson, a British epidemiologist based in Rome. That year, the swine flupandemic was spreading worldwide, and Dr. Jefferson had been hired by the British and Australian governments to update an earlier review of Tamiflu, a drug produced by the Swiss company Roche, aimed at reducing the flu’s severity and preventing more serious complications. He asked if Dr. Doshi wanted to help.

Determining Tamiflu’s efficacy had significant economic as well as health consequences. Around the world, private companies and governments — including that of the United States — were stockpiling Tamiflu in case of influenza outbreaks, and their spending accounted for almost 60 percent of the drug’s $3 billion in sales in 2009.


Archie Cochrane, an influential British epidemiologist.CreditCochrane Archive, Cardiff University Library, University Hospital Llandough

The review of Tamiflu was being conducted under the auspices of the Cochrane Collaboration, a well-regarded network of independent researchers, including Dr. Jefferson, who evaluate medical treatments’ effectiveness by analyzing all available research.

At the time, Dr. Doshi knew little about clinical trials or even much about the drug industry. But he knew Dr. Jefferson. Dr. Doshi, after receiving undergraduate and master’s degrees in anthropology and East Asian studies from Brown and Harvard, had shifted focus and was pursuing a doctorate at M.I.T., studying the intersection of medicine and politics. He met Dr. Jefferson, a prominent skeptic of the flu vaccineafter researching whether the Centers for Disease Control was exaggerating the deadliness of the disease.

“We were both lone wolves in the field of influenza,” Dr. Doshi recalled.

Dr. Jefferson had conducted a Cochrane review of Tamiflu’s effectiveness a few years earlier, concluding that the drug reduced the risk of complications from the flu. He assured Dr. Doshi and other researchers on his team that the update would be fairly simple.

But just as their work was getting under way, a simple comment arrived on the Cochrane Web site that changed the course of the research and would ultimately fuel a worldwide effort to force drug companies to be more transparent.

The author of that comment, Dr. Keiji Hayashi, had no connection to the Cochrane group; he was a pediatrician in Japan who had prescribed Tamiflu to children in his practice, but had come to question its efficacy. He was curious about one of the main studies on which Dr. Jefferson had relied in his previous analysis. Called the Kaiser study, it pooled the results of 10 clinical trials. But Dr. Hayashi noticed that the results of only two of those trials had been fully published in medical journals. Given that details of eight trials were unknown, how could the researchers be certain of their conclusion that Tamiflu reduced risk of complications from flu?

“We should appraise the eight trials rigidly,” Dr. Hayashi wrote.

Reviews by the Cochrane group are known for being among the most thoroughly researched medical analyses available. But in trying to answer the pediatrician’s question, Dr. Jefferson realized that there was a flaw: they relied too heavily on the assumption that the articles published in journals accurately represented the results of all clinical trials that had been conducted.

As he tried to track down the authors of the Kaiser study and the two published trials, Dr. Jefferson said he hit dead ends: One author said he had moved offices and no longer had the files; another said he had never seen the primary trial data, instead relying on a summary analysis provided by Roche. All the authors suggested that he contact the company.

“We took it on faith — on trust,” Dr. Jefferson, 59, said recently in a phone interview. Dr. Hayashi’s question had tested that faith. Dr. Jefferson began typing each new discovery in a private journal he called Hayashi’s Problem, which, he said, “charted my transformation from Dr. Jekyll to Mr. Hyde.”

Dr. Doshi said that medicine “relies on hierarchies of trust.” He added: “A patient is not going to be in a position to review the entire evidence base themselves. But they trust that there is a watchdog out there.”

As they dug into the Tamiflu research, Dr. Doshi said, he realized that such a watchdog didn’t exist. Instead, he said, “we have partial watchdogs who see part of the full picture.” It became his mission to see the full picture.

Having struck out with the authors of the disputed Kaiser paper and the two other published trials, Dr. Jefferson approached Roche itself, asking for the underlying data from the missing trials. But when he declined to sign a confidentiality agreement, Roche decided not to cooperate with the researchers.

Without more complete data about the clinical trials, the Cochrane group decided that it could not include the disputed study that summarized those results. In December 2009, the team reported that Tamiflu could not be shown to reduce complications like pneumonia or hospitalizations.


CreditJulia Yellow

The British Medical Journal, which printed the team’s conclusions, also published its own investigation, showing that Roche had hired ghost writers to author some of the articles involving Tamiflu, and that those writers had said they were under pressure to highlight positive messages about the drug. Roche responded that hiring such writers was common industry practice at the time of the articles, and it rejected the idea that they had been pressured to write positively about the drug.

The articles in the British journal created a sensation, and the Cochrane Collaboration’s efforts became a cause célèbre. “Everyone knows about publication bias,” said Dr. Steven Woloshin, a professor of medicine at the Dartmouth Institute for Health Policy and Clinical Practice and an advocate of more widespread sharing of clinical trial data. “But they just had so much energy and they brought so much attention to it.”

The group’s efforts seemed to make a difference: After the articles in the British journal, Roche turned over partial copies of study reports, amounting to a little more than 3,000 pages. Then, in 2011, the European Medicines Agency turned over more than 22,000 pages of documents for 19 trial reports to Dr. Jefferson and his team.

The door had been opened. As they read through the records, the researchers discovered the importance of documents called clinical study reports, which are thousands of pages long and contain details as varied as descriptions of trial protocol and design and the ingredients of the placebo pills.

“We used to know that there was a published paper and there were data behind it,” said Dr. Fiona Godlee, the editor of the British Medical Journal. “But people haven’t talked about these things, like clinical study reports, that are now being talked about a great deal.” Last fall, the journal said it would publish the results of clinical trials only if drug companies and researchers agreed to provide data upon request.

In April, Roche said it would make available to the Cochrane researchers clinical study reports for all Roche-sponsored trials of Tamiflu. Dr. Jefferson, Dr. Doshi and their colleagues hope to complete another update to their review of the drug by year-end.

Some said it was a shame that it took this long for the company to relent. “All these years later, and we still don’t know if Tamiflu is effective,” said Dr. Harlan Krumholz, the Yale cardiologist who oversaw the review of Medtronic’s bone treatment. “It’s perplexing to have a billion-dollar drug, and you’re still not willing to share everything you’ve got to know whether this thing is effective and safe.”

THOUGH the Tamiflu question is not yet resolved, the Cochrane researchers have succeeded in a bigger way: by helping to change the conversation around companies’ responsibility to reveal drug trial data.

Drug companies do not always credit the Cochrane Collaboration. In February, Roche followed Glaxo’s lead and announced that it, too, would release detailed clinical data to outside researchers, upon request. But Daniel O’Day, chief operating officer of pharmaceuticals at Roche, denied that its pledge had been motivated by the Tamiflu experience. He said Roche has provided data to “thousands” of researchers.

Mr. O’Day said “there were probably errors on both sides” in how the Cochrane researchers and Roche communicated with each other, and said the relationship deteriorated after Dr. Jefferson refused to sign a confidentiality agreement. He said the company was trying to rebuild its relationship with the Cochrane researchers, but that it stood by the safety and efficacy of Tamiflu.

In 2010, Roche commissioned researchers at the Harvard School of Public Health to conduct a re-analysis of Tamiflu clinical data, which largely confirmed the positive conclusions of the Kaiser study.

Mr. O’Day asserted that the company’s transparency pledge had arisen from “the call from society in general for greater transparency of the clinical trials that we have.” But others say the Cochrane researchers are largely responsible for that call for transparency.


Tom Jefferson, an epidemiologist, worked with Dr. Doshi in reviewing research about Tamiflu’s effectiveness. CreditChris Warde-Jones for The New York Times

Andrew Witty, Glaxo’s C.E.O., said in an interview that his promise to provide detailed clinical data had grown out of a companywide effort, initiated soon after he became chief in 2008, that would “really ensure that we were more in step with where I thought, frankly, society and the world was moving.”

Glaxo, moreover, was in need of an image rehabilitation. Last year, it pleaded guilty to criminal charges and agreed to pay $3 billion in fines after the United States Justice Department accused the company, based in London, of failing to report safety data about its diabetes drug Avandia, and of publishing misleading information about Paxil, the antidepressant, in a medical journal. The settlement, which also included civil penalties over marketing of other drugs, was the largest ever involving a pharmaceutical company.

“We don’t see any reason for this information to be held out of the public domain,” Mr. Witty said, “provided that the people who are interrogating the information are legitimate researchers with a legitimate question to ask.”

In a twist, Roche now finds itself on the same side as the Cochrane researchers — and against many in its own industry — in a debate over what kind of data the European Medicines Agency should be making public. On Monday, the agency released a draft policy, expected to take effect next year, in which it would release clinical trial data whenever it approved a new drug. While Roche and Glaxo have supported the policy, the Pharmaceutical Research and Manufacturers of America, a major industry group, and other drug companies have opposed it.

John J. Castellani, chief executive of PhRMA, said the industry had championed open-source efforts to develop better methods for testing cancer drugs, for example. But proposals like those from the Cochrane team and the European agency go too far, he said.

“If you dump onto the sidewalk all the data and you include commercially protected information,” he said, “then you’re essentially giving to competitors what we invested billions of dollars in.”

Others warned that such a policy could discourage drug companies from investing in Europe. “If you, on the other hand, say, ‘You guys are bad actors, we want to cut your prices, we want to take your confidential data and share it with any one of your competitors,’ you don’t get the same feeling of encouragement,” Christopher A. Viehbacher, C.E.O. of the French pharmaceutical company Sanofi, told reporters in Brussels on Monday, according to Reuters.

Industry officials and regulators in the United States say the public already has access to vast amounts of information about clinical trials. The basic results of all clinical trials must now be registered in a federal clearinghouse, for example, and the Food and Drug Administration publishes staff reviews and other documents when it approves a new drug. The F.D.A. has said that it is monitoring the developments in Europe but that federal laws in the United States restrict what types of information can be released, particularly data that could reveal personal or commercially confidential information.

Cochrane group members point to the Medtronic study as an example of the value of a neutral perspective.

In 2011, Medtronic awarded a $2.5 million grant to Yale and asked it to oversee a detailed review of trial data for Infuse, a bioengineered material in spinal fusions to treat back pain. The company was facing claims that it had published misleading information about the treatment, and it turned over its data in an effort to address those criticisms. Two teams that examined the data came to similar conclusions: Infuse appeared to be no better than an older treatment, and may pose added risks.

EARLIER this month, Dr. Doshi opened what he hopes will be a new chapter in his quest for greater understanding of clinical trials. He and several other researchers published what amounted to an ultimatum to drug companies: publish your data, or we’ll do it for you.

Under the plan, researchers would publish articles summarizing trial results in cases where the underlying data has already been released. In isolated cases, such information has been made public through litigation and Freedom of Information Act requests.

“It’s really neat to see a larger opportunity for a larger impact,” he said. “Tamiflu just happened to be the lever that opened that door.”


This article was originally published in The New York Times.  Read the original article.

Scientists have decoded the genome of the axolotl, the Mexican amphibian with a Mona Lisa smile.

Scientists have decoded the genome of the axolotl, the Mexican amphibian with a Mona Lisa smile. It has 32 billion base pairs, which makes it ten times the size of the human genome, and the largest genome ever sequenced.

The axolotl, endangered in the wild, has been bred in laboratories and studied for more than 150 years. It has the remarkable capacity to regrow amputated limbs complete with bones, muscles and nerves; to heal wounds without producing scar tissue; and even to regenerate damaged internal organs.

This salamander can heal a crushed spinal cord and have it function just like it did before it was damaged. This ability, which exists to such an extent in no other animal, makes its genes of considerable interest.

Now researchers, using one genetic sequencing technique to do their analysis and then another to “proof read” it, have provided researchers with the tools to study and manipulate the genes of the axolotl. Their study appears in Nature.

“The techniques in this paper are all at the cutting edge,” said Ryan Kerney, a biologist at Gettysburg College who has published widely on amphibian genetics but was not involved in this study. “And the data they generated are incredibly thorough for any genome, much less one this large.”

This is the first salamander genome ever sequenced. The reason it took so long is that it has so many repetitive parts, according to Elly M. Tanaka, a senior scientist at the Research Institute of Molecular Pathology in Vienna and senior author of the new study. The study was a huge computational effort, requiring techniques developed expressly for the purpose.

“We want to understand the huge changes in the RNA and proteins that the cells produce to change from an adult cell to a stem cell,” Dr. Tanaka said. “How does an injury cause such a huge change? We can’t understand that without knowing how different parts of the genome are used to change how cells behave.”

The researchers have identified some of the genes involved in regeneration, and some genes that exist only in the axolotl, but there is much work still to be done.

“The adventure is just starting,” Dr. Tanaka said. “Completing the genome will open up a wealth of opportunities in studying how organisms regenerate. We’re just as excited as people were when they first decoded the human genome.”

This article was originally published in The New York Times.  Read the original article.

The Earth Biogenome Project aims to sequence the DNA of all the planet’s eukaryotes, some 1.5 million known species including all known plants, animals and single-celled organisms.

Of the estimated 15 million eukaryotic species, only 10 percent have been taxonomically classified. Of that percentage, scientists have sequenced the genomes of around 15,000 species, less than 0.1 percent of all life on Earth.

“The partnership will construct a global biology infrastructure project to sequence life on the planet to enable solutions for preserving the Earth’s biodiversity, managing ecosystems, spawning bio-based industries and sustaining human societies,” said Lewin, who chairs the Earth BioGenome Project working group. Lewin holds appointments in the Department of Evolution and Ecology and the UC Davis Genome Center.

Protecting and preserving the Earth’s biodiversity

Harris Lewin, distinguished professor of evolution and ecology at UC Davis, chairs the the Earth BioGenome Project working group. The Earth BioGenome Project will partner with the Earth Bank of Codes to sequence the genomes of all eukaryotic life on Earth over the next 10 years. The partnership was announced at the World Economic Forum in Davos, Switzerland on Jan. 23, 2018.
Credit: Gregory Urquiaga/UC Davis

The Earth Bank of Codes will make this biological data available to bio-innovators around the world. The goal is to unlock the potential of the planet’s biodiversity while advancing the marketplace for bio-inspired chemicals, materials, processes and innovations capable of solving some of the most pressing issues facing humanity.

The partnership between the Earth BioGenome Project and the Earth Bank of Codes is part of the World Economic Forum’s 4IR for the Earth Initiative.

“The Fourth Industrial Revolution has the transformational power to unlock economic value that was previously inaccessible, by decoding nature’s DNA and by learning from its function and processes,” said Juan Carlos Castilla-Rubio, a member of the World Economic Global Future Council on the Environment and Natural Resource Security. “Scientists and entrepreneurs are now able to tap into a new source of knowledge that could be the driver behind the next generation of novel technologies.”

Recent advances in genomic sequencing and falling technology prices have created an advantageous opportunity to pursue the project.

As a proof of concept project, Lewin and partners have organized the Amazon Bank of Codes initiative in the Amazon basin. The pilot project aims to offer indigenous and traditional communities an opportunity to reap a fair share of the economic value generated from the use of biological data and natural assets from their local biomes.


This article was originally published in NIH. Read the original article.