YEAR OF MIRACLES

Ever since 1900, when Gregor Mendel’s work on peas and inheritance was rediscovered, scientists have regarded the “gene” as the fundamental unit of heredity (just as the atom was regarded as the bedrock of pre-Einsteinian physics). Crick and Watson’s discovery of the DNA double helix as the carrier of hereditary information did little to disturb the status quo. In recent months, however, a perfect storm of new technology and research has blown apart 20th-century dogma. The notion of the Mendelian gene as a unit of heredity, scientists now realise, is a fiction.

Many scientists now believe that heredity is the result of an incredibly complex interplay among the basic components of the genome, scattered among many different genes and even the vast stretches of “junk DNA” once thought to serve no purpose. Biology has been building up to this insight for years, but some big puzzle pieces have now fallen into place. Once scientists abandoned their preconceived notions of genes and looked instead at individual DNA “letters” in the genome—the four bases A, C, T and G— they immediately began to see cause-and-effect connections to myriad diseases and human traits.
The result of this seemingly modest conceptual breakthrough has been a torrent of new discoveries. In five months this year, from April through August, geneticists at the Harvard/MIT Broad Institute, founded by Eric Lander; at deCODE Genetics in Iceland, founded by Kari Stefansson, and several other institutions have published papers suggesting that the key to a deeper understanding of the human genome may finally be in hand. These scientists have identified specific alterations in the sequence of DNA that play causative roles in a broad range of common diseases, including type 1 and type 2 diabetes; schizophrenia; bipolar disorder; glaucoma; inflammatory bowel disease; rheumatoid arthritis; hypertension; restless legs syndrome; susceptibility to gallstone formation; lupus; multiple sclerosis; coronary heart disease; colorectal, prostate and breast cancer, and the pace at which HIV infection causes full-blown AIDS. Unlike so many previous “disease gene” discoveries, these findings are being replicated and validated. “The race to discover disease-linked genes reaches fever pitch,” declared the leading British science journal Nature. Its American counterparts at Science chimed in: “After years of chasing false leads, gene hunters feel they have finally cornered their prey. They are experiencing a rush this spring as they find, time after time, that a new strategy is enabling them to identify genetic variations that likely lie behind common diseases.” That the world’s top two scientific journals still use the old language of “genes” to describe these discoveries shows how new the new thinking really is.
These findings are just a prelude to what’s shaping up as a true conceptual and technological revolution. Just as physics shocked the world in the 20th century, it is now clear that the life sciences will shake up the world in the 21st. In a handful of years, your doctor may be able to run a computer analysis of your personal genome to get a detailed profile of your health. This goes well beyond merely making predictions. A new technology called RNA interference may also allow doctors to control how your DNA is “expressed,” helping you circumvent potential health risks. Many common diseases that have preyed on humans for eons—devastating neurological conditions such as Alzheimer’s, Parkinson’s, cancer—could be eradicated. If this sounds outrageously optimistic, so did the promise of eliminating smallpox and polio to previous generations.

Why is all this happening now?What has changed between this year and last? To answer these questions, we need to trace the story of how mainstream biomedical scientists tried to link the cause of diseases to single genes and, despite early success, hit a brick wall. Meanwhile, a handful of renegade scientists, pursuing their own pet projects, happened to develop exactly the intellectual tools needed to break through that wall. These biologists are now the leaders of the new revolution in biomedical science.
The seeds of our new understanding were first sown in the 1960s, when molecular biologists figured out how genetic information is organised, regulated and reproduced inside single-cell bacteria. In bacteria, a gene is a discrete segment of DNA that contains the “code” that tells the cell how to make a particular type of protein. Bacterial genes are arranged along a single DNA molecule, with only tiny gaps in between. Since all organisms have DNA and work by essentially the same biochemistry, scientists assumed that a human genome would look like a larger version of a bacterium’s.
Clues that something was amiss came quickly with the development of DNA-sequencing methods in the 1970s. The first surprising result was: genes accounted for only 2 per cent of the human genome —the rest of the DNA didn’t seem to have any purpose at all. Biologists Phillip Sharp and Richard Roberts made things worse with a discovery that won them a Nobel Prize in 1993. If the gene were the basic unit of heredity, the DNA required to make any particular protein should be contained in its corresponding gene. But Sharp and Roberts found DNA codes for individual proteins are often split and scattered throughout the genome.
A visionary physician-scientist named Leroy Hood, now at the Institute for Systems Biology in Seattle, grasped the far-reaching implications of a fundamental fact: while even the simplest organism is immensely complicated, the primary structures of its most complicated parts — DNA and proteins — are very simple. The alphabet of DNA contains only the four chemical letters (or bases) A, C, G and T, and proteins are made from just 21 amino acids. Hood saw that this simplicity would make it possible for robots and computers to read and write DNA and proteins more quickly, accurately and cheaply than human beings.
Hood completely transformed the biomedical enterprise. DNA-writing machines give genetic engineers an unlimited capacity to create novel genes that can be studied in test tubes or added to the genomes of living organisms. And protein-writing and -reading machines provided drug firms with the ability to create a new generation of protein-based drugs. The DNA-reading machines suddenly made it conceivable to crack the 3 billion-base sequence of an entire human genome. In 1990 the U.S. government embarked on a 15-year, $3 billion project to do just that.
Eight years later, however, the project — parceled out to many US scientists — was still less than 10 percent complete. Now it was biotech entrepreneur Craig Venter who was frustrated. Convinced that government-funded workers were the problem rather than the solution, Venter enlisted private funding of $200 million to build an enormous lab filled with hundreds of automated machines, working 24/7, overseen by a handful of technicians. Within three years, the first reading of a human genome was essentially complete.
Armed with data from the genome project, scientists figured they’d surely be able to crack the really hard diseases, like cancer and heart disease. But a funny thing happened when they began to look closely at this vast storehouse of genetic information. Geneticists Andrew Fire and Craig Melo galvanised the field by discovering a key mechanism that had been completely overlooked— the cellular process of RNA interference. (They shared a Nobel Prize in 2006 for the work.)
Geneticists had taken for granted that the machinery of cells involved genes directing the production of proteins, and proteins doing the work of the cell. Here was a process that didn’t involve proteins at all. Instead, tens of thousands of hitherto mysterious regions of the human genome — part of the so-called junk DNA — directed the production of specific molecules called microRNAs (consisting of bits of RNA, a well-known component of cells). These microRNAs then oversaw a whole new process, called RNA interference (RNAi), that served to modulate the expression of DNA.
The good news was that RNAi could open up a whole new approach to biomedical therapy (more on that later). But RNAi also made it clear that the fundamental unit of heredity and genetic function is not the gene but the position of each individual DNA letter.
To make it all harder to fathom, each bit of DNA is susceptible to mutation and variation among individuals. Of the 3 billion DNA bases in the human genome, geneticists identified about one tenth of one percent (millions) that differ from one person to another. Variations in these particular letters — called “snips,” or SNPs, for single nucleotide polymorphisms — have replaced genes as the unit of heredity.
Many scientists responded to this devastating realization by going into a funk. Fortunately, another visionary scientist, Kari Stefansson of Iceland, was already blazing a trail out of this thicket. If the genome was far more complex than scientists had thought, they would need to test for many more variables, and to do that they would need more test subjects. To find the cause of diseases would now require the participation of very large groups of genetically related people.
Stefansson decided to solve this problem by taking aim at the largest well-documented extended family that he knew — his own. Nearly all the 300,000 citizens of Iceland can trace their ancestors back, through detailed, public genealogical records, to the Vikings who settled this desolate European island more than 1,000 years ago. He persuaded the Icelandic government to provide his company, decode, with exclusive access to the health records of its citizens in return for bringing investment capital and hi-tech jobs to the capital, Reykjavik. So far, more than 100,000 Icelandic volunteers have donated their DNA to deCODE.

The power of large numbers was soon apparent. In a study of obesity, Stefannson directed his software to look for SNPs associated with subsets of the population who were either extremely overweight or very thin. Within just a few hours, it began finding evidence that variations among particular DNA letters indeed played a causative role, confirming SNPs as the new unit of inheritance.
As of September, deCODE has made progress in identifying SNPs that may play a role in 28 common diseases, including glaucoma, schizophrenia, diabetes, heart disease, prostate cancer, hypertension and stroke. In some cases, such as glaucoma and prostate cancer, deCODE’s findings could lead to diagnostic tests for identifying people at risk of developing the disease. In other instances, such as schizophrenia, links to particular proteins have led to insight about the cause of the disease, which could lead to therapies.
Buoyed by Stefansson’s success, other geneticists were eager to perform large-scale family studies, yet few had similar access to ancient genealogical records. But serendipity would deliver an epiphany: it’s possible to study the entire human population as a single extended family, provided scientists collect enormous amounts of data. Eric Lander, an MIT professor and the intellectual leader of the US government effort to sequence the first human genome, realised scaling up would require a new approach. In 2004, Lander persuaded MIT and Harvard to combine their enormous resources toward the creation of the Broad Institute. Backed by $200 million from billionaire philanthropists Eli and Edythe Broad, the institute is driving the development of ever more advanced genetic technologies. One technology, based on computer-chip fabrication, can identify DNA base letters present at 500,000 SNPs in the genomes of 40,000 or more people.
Think of this as a spreadsheet with 500,000 columns (each representing a specific SNP) and 40,000 rows (one for each person). To hunt for a genetic basis for, say, bipolar disease, the computer searches rows of people who have the disorder, checking column by column for an unusually high frequency of particular letters in comparison with people without the disease. As it turns out, a collaboration of American and German researchers has done this work—and found that variations of DNA letters in 20 different positions are influential in bipolar disease.
Incredibly, most disease-causing variants are the most common ones present in the human population: the strongest-acting one, for instance, exists in 80 percent of people without bipolar disease and 85 percent of people with the disease. The implication is that these variants are beneficial in some way, and cause problems only when their number exceeds a threshold.
To make sense of this complexity, scientists would like ultimately to build a vast international database that contains the complete sequence of DNA bases in the genomes of hundreds of millions of people. Ideally, such a database would be available for analysis by all biomedical researchers and would provide the foundation for understanding the genetic components of all human traits. That sounds like a lot of data — think of a spreadsheet with 3 billion columns and 100 million rows — but computing power is getting cheaper by the year.
The explosion of genetic discoveries shows no sign of letting up any time soon. New diseases are being added to the list every month, and biologists are rapidly parlaying gene- and SNP-disease links into a deeper understanding of how proteins and other molecules can misbehave to cause different medical problems in different people. Other scientists are working to advance the biology revolution (accompanying interviews). As a result of their efforts, many children born this year could very well be alive and healthy at the dawn of the next century, when they may look back in awe at the annus mirabilis of biomedical genetics in 2007.

-LEE SILVER (Newsweek)

MIT and Novartis in new partnership aimed at transforming pharmaceutical manufacturing

Novartis and the Massachusetts Institute of Technology have launched a long-term research collaboration aimed at transforming the way pharmaceuticals are produced.

The 10-year partnership, known as the Novartis-MIT Center for Continuous Manufacturing, will work to develop new technologies that could replace the conventional batch-based system in the pharmaceuticals industry - which often includes many interruptions and work at separate sites - with continuous manufacturing processes from start to finish.

The Novartis-MIT Center for Continuous Manufacturing combines the industrial expertise of Novartis with MIT's leadership in scientific and technological innovation. Novartis will invest USD 65 million in research activities at MIT over the next 10 years.

"This partnership demonstrates our commitment to lead not only in discovering innovative treatments for patients but also in improving manufacturing processes, which are critical to ensuring a high-quality, efficient and reliable supply of medicines to patients. Our collaboration with MIT, a worldwide leader in developing cutting edge technologies, holds the promise to achieve a quantum leap in the production of pharmaceuticals, a field which has received rather little attention in the past," said Dr. Daniel Vasella, Chairman and CEO of Novartis.

Novartis and MIT expect the technologies created in this collaboration will benefit patients and healthcare providers through a positive impact on supply availability and the quality of medicines. These technologies will also seek to reduce the environmental impact of manufacturing activities.

"The Novartis-MIT Center for Continuous Manufacturing has the potential to revolutionize drug development and production," said Susan Hockfield, MIT President. "We are delighted to collaborate with Novartis to help improve the way that drugs are manufactured so that patients have quicker and more reliable access to the medications they need. The new educational opportunities that this program will provide for our students make this partnership even more exciting."

The pharmaceutical industry currently uses batch-based manufacturing that has been common for several years, even though other industries have moved to continuous manufacturing.

In this often time-consuming process, pharmaceutical active ingredients are synthesized in a chemical manufacturing plant. These ingredients are then shipped to a manufacturing facility, often at another site, where they are converted through defined processes into giant batches of pills, liquid or cream. With multiple interruptions, including transport to separate locations, each batch may take weeks to produce. In addition, manufacturing design and scale-up for a new drug are very costly and time-consuming.

Expected benefits of continuous manufacturing include accelerating the introduction of new drugs by designing production processes earlier; using smaller production facilities, with lower building and capital costs; minimizing waste, energy consumption and raw material use; monitoring quality assurance on a continuous basis instead of post-production batch-based testing; and enhancing process reliability and flexibility to respond to market needs.

The initial research of the Novartis-MIT Center for Continuous Manufacturing will be conducted primarily through Ph.D. programs at MIT laboratories, and then transferred to Novartis for further development to industrial-scale projects.

The partners expect the Center's work to involve seven to ten MIT faculty members, as well as students, postdoctoral fellows and staff scientists. Novartis will commit its manufacturing and R&D resources and will pilot new manufacturing processes with one of its pharmaceutical products.

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