Tag Archives: genomics

Microbiome Apps Personalize EAT recommendations

Richard Sprague provides a useful update about the microbiome landscape below. Microbiome is exploding. Your gut can be measured, and your gut can influence your health and well-being. But now …. these gut measurements can offer people a first: personalized nutrition information.

Among the more relevant points:

– Israel’s Weitzman Institute is the global leader academically. Eran Elinav, a physician and immunologist at the Weizmann Institute and one of their lead investigators (see prior post).
– The older technology for measuring the gut is called “16S” sequencing. It tell you at a high level which kinds of microbes are present. It’s cheap and easy, but 16S can see only broad categories,
– The companies competing to measure your microbiome are uBiome, American Gut, Thryve, DayTwo and Viome. DayTwo and Viome offer more advanced technology (see below).
– The latest technology seems to be “metagenomic sequencing”. It is better because it is more specific and detailed.
– By combining “metagenomic sequencing” information with extensive research about how certain species interact with particular foods, machine-learning algorithms can recommend what you should eat.
– DayTwo offers a metagenomic sequencing for $299, and then combines that with all available research to offer personalized nutrition information.
– DayTwo recently completed a $12 million financing round from, among others, Mayo Clinic, which announced it would be validating the research in the U.S.
– DayTwo draws its academic understandings from Israel’s Weitzman Institute. The app is based on more than five years of highly cited research showing, for example, that while people on average respond similarly to white bread versus whole grain sourdough bread, the differences between individuals can be huge: what’s good for one specific person may be bad for another.

CREDIT: Article on Microbiome Advances

When a Double-Chocolate Brownie is Better for You Than Quinoa

A $299 microbiome test from DayTwo turns up some counterintuitive dietary advice.

Why do certain diets work well for some people but not others? Although several genetic tests try to answer that question and might help you craft ideal nutrition plans, your DNA reveals only part of the picture. A new generation of tests from DayTwo and Viome offer diet advice based on a more complete view: they look at your microbiome, the invisible world of bacteria that help you metabolize food, and, unlike your DNA, change constantly throughout your life.
These bugs are involved in the synthesis of vitamins and other compounds in food, and they even play a role in the digestion of gluten. Artificial sweeteners may not contain calories, but they do modify the bacteria in your gut, which may explain why some people continue to gain weight on diet soda. Everyone’s microbiome is different.

So how well do these new tests work?
Basic microbiome tests, long available from uBiome, American Gut, Thryve, and others, based on older “16S” sequencing, can tell you at a high level which kinds of microbes are present. It’s cheap and easy, but 16S can see only broad categories, the bacterial equivalent of, say, canines versus felines. But just as your life might depend on knowing the difference between a wolf and a Chihuahua, your body’s reaction to food often depends on distinctions that can be known only at the species level. The difference between a “good” microbe and a pathogen can be a single DNA base pair.

New tests use more precise “metagenomic” sequencing that can make those distinctions. And by combining that information with extensive research about how those species interact with particular foods, machine-learning algorithms can recommend what you should eat. (Disclosure: I am a former “citizen scientist in residence” at uBiome. But I have no current relationship with any of these companies; I’m just an enthusiast about the microbiome.)

I recently tested myself with DayTwo ($299) to see what it would recommend for me, and I was pleased that the advice was not always the standard “eat more vegetables” that you’ll get from other products claiming to help you eat healthily. DayTwo’s advice is much more specific and often refreshingly counterintuitive. It’s based on more than five years of highly cited research at Israel’s Weizmann Institute, showing, for example, that while people on average respond similarly to white bread versus whole grain sourdough bread, the differences between individuals can be huge: what’s good for one specific person may be bad for another.

In my case, whole grain breads all rate C-. French toast with challah bread: A.

The DayTwo test was pretty straightforward: you collect what comes out of your, ahem, gut, which involves mailing a sample from your time on the toilet. Unlike the other tests, which can analyze the DNA found in just a tiny swab from a stain on a piece of toilet paper, DayTwo requires more like a tablespoon. The extra amount is needed for DayTwo’s more comprehensive metagenomics sequencing.

Since you can get a microbiome test from other companies for under $100, does the additional metagenomic information from DayTwo justify its much higher price? Generally, I found the answer is yes.

About two months after I sent my sample, my iPhone lit up with my results in a handy app that gave me a personalized rating for most common foods, graded from A+ to C-. In my case, whole grain breads all rate C-. Slightly better are pasta and oatmeal, each ranked C+. Even “healthy” quinoa — a favorite of gluten-free diets — was a mere B-. Why? DayTwo’s algorithm can’t say precisely, but among the hundreds of thousands of gut microbe and meal combinations it was trained on, it finds that my microbiome doesn’t work well with these grains. They make my blood sugar rise too high.

So what kinds of bread are good for me? How about a butter croissant (B+) or cheese ravioli (A-)? The ultimate bread winner for me: French toast with challah bread (A). These recommendations are very different from the one-size-fits-all advice from the U.S. Department of Agriculture or the American Diabetes Association.

I was also pleased to learn that a Starbucks double chocolate brownie is an A- for me, while a 100-calorie pack of Snyder’s of Hanover pretzels gets a C-. That might go against general diet advice, but an algorithm determined that the thousands of bacterial species inside me tend to metabolize fatty foods in a way that results in healthier blood sugar levels than what I get from high-carb foods. Of course, that’s advice just for me; your mileage may vary.

Although the research behind DayTwo has been well-reviewed for more than five years, the app is new to the U.S., so the built-in food suggestions often seem skewed toward Middle Eastern eaters, perhaps the Israeli subjects who formed the original research cohort. That might explain why the app’s suggestions for me include lamb souvlaki with yogurt garlic dip for dinner (A+) and lamb kabob and a side of lentils (A) for lunch. They sound delicious, but to many American ears they might not have the ring of “pork ribs” or “ribeye steak,” which have the same A+ rating. Incidentally, DayTwo recently completed a $12 million financing round from, among others, Mayo Clinic, which announced it would be validating the research in the U.S., so I expect the menu to expand with more familiar fare.

Fortunately you’re not limited to the built-in menu choices. The app includes a “build a meal” function that lets you enter combinations of foods from a large database that includes packaged items from Trader Joe’s and Whole Foods.

There is much more to the product, such as a graphical rendering of where my microbiome fits on the spectrum of the rest of the population that eats a particular food. Since the microbiome changes constantly, this will help me see what is different when I do a retest and when I try Viome and other tests.

I’ve had my DayTwo results for only a few weeks, so it’s too soon to know what happens if I take the app’s advice over the long term. Thankfully I’m in good health and reasonably fit, but for now I’ll be eating more strawberries (A+) and blackberries (A-), and fewer apples (B-) and bananas (C+). And overall I’m looking forward to a future where each of us will insist on personalized nutritional information. We all have unique microbiomes, and an app like DayTwo lets us finally eat that way too.

Richard Sprague is a technology executive and quantified-self enthusiast who has worked at Apple, Microsoft, and other tech companies. He is now the U.S. CEO of an AI healthcare startup, Airdoc.

====================APPENDIX: Older Posts about the microbiome =========

Microbiome Update
CREDIT: https://www.wsj.com/articles/how-disrupting-your-guts-rhythm-affects-your-health-1488164400?mod=e2tw A healthy community of microbes in the gut maintains regular daily cycles of activities. A healthy community of microbes in the gut maintains regular daily cycles of activities.PHOTO: WEIZMANN INSTITUTE By LARRY M. GREENBERG Updated Feb. 27, 2017 3:33 p.m. ET 4 COMMENTS New research is helping to unravel the mystery of how […]

Vibrant Health measures microbiome

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Microbiome Update
My last research on this subject was in August, 2014. I looked at both microbiomes and proteomics. Today, the New York Times published a very comprehensive update on microbiome research: Link to New York Time Microbiome Article Here is the article itself: = = = = = = = ARTICLE BEGINS HERE = = = […]

Microbiomes
Science is advancing on microbiomes in the gut. The key to food is fiber, and the key to best fiber is long fibers, like cellulose, uncooked or slightly sauteed (cooking shortens fiber length). The best vegetable, in the view of Jeff Leach, is a leek. Eating Well Article on Microbiome = = = = = […]

Arivale Launches LABS company
“Arivale” Launched and Moving Fast. They launched last month. They have 19 people in the Company and a 107 person pilot – but their plans are way more ambitious than that. Moreover: “The founders said they couldn’t envision Arivale launching even two or three years ago.” Read on …. This is an important development: the […]

Precision Wellness at Mt Sinai
My Sinai announcement Mount Sinai to Establish Precision Wellness Center to Advance Personalized Healthcare Mount Sinai Health System Launches Telehealth Initiatives Joshua Harris, co-Founder of Apollo Global Management, and his wife, Marjorie has made a $5 million gift to the Icahn School of Medicine at Mount Sinai to establish the Harris Center for Precision Wellness. […]

Proteomics
“Systems biology…is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different….It means changing our philosophy, in the full sense of the term” (Denis Noble).[5] Proteomics From Wikipedia, the free encyclopedia For the journal […]

Alzheimer’s Genetic Risk Assessment

CREDIT: NPR article

CREDIT: Bill Gates 11.13.17 Blog Post on Alzheimer’s

FDA Approves Marketing Of Consumer Genetic Tests For Some Conditions

April 7, 20171:40 PM ET
JESSICA BODDY

23andMe is now allowed to market tests that assess genetic risks for 10 health conditions, including Parkinson’s and late-onset Alzheimer’s diseases.
Meredith Rizzo/NPR
The U.S. Food and Drug Administration approved 23andMe’s personal genetic test for some diseases on Thursday, including Alzheimer’s, Parkinson’s and celiac diseases.
The tests assess genetic risk for the conditions but don’t diagnose them, the FDA says. The agency urges consumers to use their results to “help to make decisions about lifestyle choices or to inform discussions with a health care professional,” according to a press release about the decision.
Jeffrey Shuren, the director of the FDA’s Center for Devices and Radiological Health, wrote, “it is important that people understand that genetic risk is just one piece of the bigger puzzle, it does not mean they will or won’t ultimately develop a disease.” Other known factors that can play into the development of disease include diet, environment and tobacco use.

SHOTS – HEALTH NEWS
23andMe Bows To FDA’s Demands, Drops Health Claims
The FDA has previously scolded the company for marketing the personal genetic testing kits without the agency’s consent. In 2013, the agency told 23andMe to stop selling its personal genome kits in the United States until they gained FDA approval by proving they were accurate.
The company agreed to work with the FDA, as we reported, and a recent FDA review of peer-reviewed studies found more consistent links between certain gene variants and 10 diseases, the FDA says.
As a result, the FDA is now allowing 23andMe to market tests that assess genetic risks for the following 10 diseases or conditions:
▪ Parkinson’s disease, a nervous system disorder impacting movement 

▪ Late-onset Alzheimer’s disease, a progressive brain disorder that destroys memory and thinking skills 

▪ Celiac disease, a disorder resulting in the inability to digest gluten 

▪ Alpha-1 antitrypsin deficiency, a disorder that raises the risk of lung and liver disease 

▪ Early-onset primary dystonia, a movement disorder involving involuntary muscle contractions and other uncontrolled movements 

▪ Factor XI deficiency, a blood clotting disorder 

▪ Gaucher disease type 1, an organ and tissue disorder 

▪ Glucose-6-phosphate dehydrogenase deficiency, also known as G6PD, a red blood cell condition 

▪ Hereditary hemochromatosis, an iron overload disorder 

▪ Hereditary thrombophilia, a blood clot disorder 


The company’s $199 Health and Ancestry test is available directly to consumers, without seeing a physician or genetic counselor. Consumers’ DNA is extracted from a saliva sample. After mailing in their sample, people can see their results online.
“This is an important moment for people who want to know their genetic health risks and be more proactive about their health,” said Anne Wojcicki, the CEO and co-founder of 23andMe, in a company press release.
Sharon Terry, the CEO of the Genetic Alliance, a nonprofit organization that advocates for health care for people with genetic disorders, likens it to another consumer test. “Women learn they are pregnant using a test directly marketed to them and buy it off the shelf in a drugstore,” she told NPR. “In 10 years we will marvel that this is an ‘advance’ at all. Imagine pregnancy tests being only available through a doctor!”
Robert Green, a professor of medicine at Harvard Medical School, says people should be able to access genetic information in whatever way is best for them. “Some people really want this [genetic] information on their own, and others want it through their physician,” he said. “Both those channels are legitimate. People should just be aware that this information is complicated.”
But some are still concerned about whether the genes in question actually correspond to a higher risk of disease reliably enough to warrant direct-to-consumer marketing and testing, as opposed to genetic testing with the guidance of a professional.

SHOTS – HEALTH NEWS
Don’t Get Your Kids’ Genes Sequenced Just To Keep Up

SHOTS – HEALTH NEWS
Personalizing Cancer Treatment With Genetic Tests Can Be Tricky
Some health professionals worry that consumers will “take the results and run,” as Mary Freivogel put it. Freivogel, a certified genetic counselor and the president of the National Society of Genetic Counselors, added that genetics are just “one piece to the story when it comes to developing a disease.”
Freivogel said speaking with a genetic counselor before getting tested for disease is important. “Direct-to-consumer testing takes away a pre-test conversation,” she said, where counselors can help patients think about questions like: “What do you want to know? What are you going to do with this information? Is it something you’re prepared to know, or is it going to just make you anxious?”
And it isn’t clear what consumers should do with their newly calculated disease risk, especially for conditions like Alzheimer’s for which there isn’t a cure or even a course of action to prevent the disease.
What’s more, having the genes is not the same as having the diseases the genes are associated with. A person may have genes that are associated with Alzheimer’s, for example, but that doesn’t mean he or she will ever get the disease. Conversely, some people develop Alzheimer’s without the identified risk genes.
The Alzheimer’s Association does not recommend routine genetic testing for the disease in the general population because it can’t “productively guide medical treatment.”
A genetic test result for Alzheimer’s is “not going to provide useful information even if you’re at an increased risk,” said Keith Fargo, director of scientific programs at the Alzheimer’s Association. “It’s not like there’s a drug you can take right now [to prevent the disease] or a lifestyle change you can make that you shouldn’t make anyway,” such as exercising and eating right to keep your brain healthy.
John Lehr, the CEO of the Parkinson’s Foundation, says personal genetic tests can help identify risk for Parkinson’s disease. But, he wrote in a statement following the FDA’s announcement, the foundation recommends “that people who are interested in testing first seek guidance from their doctors and from genetic counselors to understand what the process may mean for them and their families.”

Helix.com takes genomics commercial

I believe that genomics just advanced …. headed to commercialization. Read on.

I received this as a gift, and just registered my saliva sample. “Geno 2.0”. As with ancestry.com, the “hook” is they promise a profile of your ancestry. Clever – does not over-promise.

Cost …. $149?

Took 10 minutes. Very cool box, like something from Apple. Inside was an equally cool, self-addressed, stamped box. Fancy test tube inside. Coded carefully – right on the sample tube. Protected for shipment … Nice. Netflix started with a kit like this.

They have 800,000 samples so far. Partnered with National Geographic, Duke, bunch of others. I registered separately – online. Great privacy policy.

This is only the beginning….like the Internet when AOL was the only game in town, and Amazon only sold books.

Go to Helix

Helix seems to be a venture-backed company – Kleiner, Warburg Pincus, and Mayo are shown as investors.

The essence of their value proposition seems to be “products that will be offered by our partners in the future.” These products will obviously draw upon the database that is being accumulated.

Solid Scientific Advisory Board.

Duke shown as partner. National Geographic as well.

Genography.com seems to be another of their sites? Partner.

Latest on well-being convenience

I just had a great experience at a CVS Minute Clinic, which I documented here:

JCR Experience with CVS Minute Clinic

It’s been awhile since I revised this mega-trend, so here is an update.

So CVS has been busy. They changed their name to CVS Health, threw tobacco out of their store, and set out to create 900 “Minute Clinics”. These were intended to provide consumers with highly convenient access to nurse practitioners who were armed with the latest in diagnostic tools and online diagnostic protocols.

The latest? CVS now has 800 Minute Clinics in 28 states plus DC.

Walgreens now has 400 clinics. Their press recently has raised questions about whether they are rethinking their corporate strategy.
 
Seattle-based Arivale arrived on the scene in 2015, announcing their intention to revolutionize this space by brings LABS to the foreground, especially through genomics. What caught my eye then was the background of the CEO, Clayton Lewis, who was in genomics from the beginning with Genentech, and Lee Hood, who is a thought-leader in the area.
 
The latest? Well, the update on Arivale is this: they did indeed raise $40 million, and they now have a year’s experience with their “pioneers”. The pioneers are individuals who opted into this intensive longitudinal tracking. The pioneers were offered well-being coaches as well. There originally were 170 pioneers, and there now are over 1,000.

Learnings:

1. the Company says that well-being coaches are a winner. People like them and they say they really help keep them on track.  
2. They are finding that it is difficult (impossible) to keep people focused on long-term risks.
3. They are finding that “experiences” – avoiding bad experiences and promoting good “experiences” is proving useful as a way to motive the pioneers.
 
References:
I wrote about my own vision for this subject here, in 2014:

JCR 2014 Predictions
 

 I wrote about Walgreens here:
2011 post on Walmart with Updates

I Wrote about Arivale here:
2015 post on Arivale

….and here are the two co-founders, on stage in March, 2016:
Lee Hood and Clayton Lewis
 
… an astute 2016 synopsis of what Arivale has learned is here:
 
2016 synopsis of Arivale learnings
 
…and a March 2016 article provides an update, including the acquisition of the Institute for System Biology:
March 2016 Article on Arivale

A good summary on Walgreens and CVS overall is here:

Walgreens and CVS Summary

 

NantHealth Update

Allscripts invests $200M in Soon-Shiong’s NantHealth in software integration deal (updated)
By NEIL VERSEL
Post a comment / 61 Shares / Jun 30, 2015 at 1:33 PM
Patrick Soon-Shiong
Dr. Patrick Soon-Shiong
Electronic health records vendor Allscripts Healthcare Solutions has bought a 10 percent equity stake in NantHealth, the health IT arm of Dr. Patrick Soon-Shiong’s empire, for $200 million, while another Soon-Shiong company has bought $100 million worth of stock in Allscripts.

The deal, announced Tuesday, extends a partnership first disclosed in March, in which the two companies agreed to share technology in developing more personalized cancer treatments.

Chicago-based Allscripts paid cash for its 10 percent stake in NantHealth, the two companies said. Soon-Shiong bought into Allscripts via his personal investment vehicle, NantCapital, part of his burgeoning NantWorks conglomeration.

The Los Angeles Times reported that the cross-investment, which values Culver City, Calif.-based NantHealth at $2 billion, closer to a planned initial public offering later this year. “We feel we have one or two transactions to accomplish, then we will initiate the public offering that we anticipate will happen probably within this year,” Soon-Shiong reportedly told the Times.

NantHealth and Allscripts said that they would jointly integrate their software via application provider interfaces, including placing dashboards to NantHealth databases and analytics engines into Allscripts EHRs. For example, NantHealth will make its Eviti cancer-specific clinical decision support technology available through Allscripts front ends, NantHealth President Robert Watson said in an interview with MedCity News.

The two companies also plan on developing several specific pieces of technology: an ontology and industry standard for cross-clinical usage of a NantHealth-developed test known as GPS Cancer (GPS stands for genomic-proteomic sequencing); invitations for GPS Cancer sequencing delivered to specific patients through Allscripts’ FollowMyHealth portal; and a new product for accountable care organizations that promotes semantic interoperability.

“We believe that our GPS Cancer test should become a standard of care,” Watson said. It takes the kind of access to hospitals and cancer centers that Allscripts has to make it happen, Watson explained.

The test is more comprehensive than others on the market, Watson said, in that it takes into account the full genome and full exome, not just a small subset of pairs.

In a press release, Allscripts President and CEO Paul Black said:

“We’re taking an important step forward in our strategic partnership that fully aligns our resources and furthers Allscripts’ strategy to invest in new technologies that can revolutionize service to hospitals and physicians. Under the leadership of Dr. Soon-Shiong, NantHealth is pioneering extraordinarily innovative, personalized healthcare solutions that will empower more efficient and effective clinical decisions. We’re confident that our joint efforts will help Allscripts lead the way in our vision of delivering open, integrated and precision-based medical solutions to physicians and patients

============== Prior Blog Post =======

NantHealth Update
Remember Dr. Patrick Soon-Shiong and NantHealth?

He is the LA billionaire I met in 2013. I was saying “watch him make his next move” in 2013 when he came to Coke and showed a vision of how he wanted to revolutionize health care. I drove in a car with him to see if he could use some of his genomic knowledge to help my friend John Farrell live (it was too late but he really tried hard and I came to respect him as a physician and oncologist).

His vision them was for a revolution in health care based on breathtaking new genomic understandings, including how genes changed over time, combined with revolutionary new home appliances that would record cloud-based data relevant to your personal health, e.g. a scale that recorded weight and pill bottles that recorded compliance with medications.

In any event ….

Take a look at his investors – – – $320 million so far, from elite players:

I’m reminded of what Dr. Patrick Soon-Shiong is doing with NantHealth, which is a lot more opaque other than the approximate $320M of private equity money invested to date by Sovereign Wealth Fund, Kuwait Investment Authority, Verizon, Celgene, Blackberry, and Blackstone.

Proteomics

“Systems biology…is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different….It means changing our philosophy, in the full sense of the term” (Denis Noble).[5]

Proteomics
From Wikipedia, the free encyclopedia
For the journal Proteomics, see Proteomics (journal).

Proteomics is the large-scale study of proteins, particularly their structuresand functions.[1][2] Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells.

The term proteomics was first coined in 1997[3] to make an analogy with genomics, the study of the genome. The word proteome is a blend of protein and genome, and was coined by Marc Wilkins in 1994 while working on the concept as a PhD student.[4][5]

The proteome is the entire set of proteins,[4] produced or modified by an organism or system. This varies with time and distinct requirements, or stresses, that a cell or organism undergoes.

Proteomics is an interdisciplinary domain formed on the basis of the research and development of the Human Genome Project;[citation needed] it is also emerging scientific research and exploration of proteomes from the overall level of intracellular protein composition, structure, and its own unique activity patterns. It is an important component of functional genomics.

While proteomics generally refers to the large-scale experimental analysis of proteins, it is often specifically used for protein purification and mass spectrometry.

Contents [hide]
1 Complexity of the problem
1.1 Post-translational modifications
1.1.1 Phosphorylation
1.1.2 Ubiquitination
1.1.3 Additional modifications
1.2 Distinct proteins are made under distinct settings
2 Limitations of genomics and proteomics studies
3 Methods of studying proteins
3.1 Protein Detection with Immunoassays
3.2 Identifying proteins that are post-translationally modified
3.3 Determining the existence of proteins in complex mixtures
3.4 Computational methods in studying protein biomarkers
4 Establishing protein–protein interactions
5 Practical applications of proteomics
5.1 Biomarkers
5.2 Proteogenomics
5.3 Current research methodologies
6 Bioinformatics for Proteomics
7 Structural proteomics
8 Expression proteomics
9 Interaction proteomics
10 Proteomics and System Biology
11 Current Proteomic Technologies
11.1 Mass Spectrometry and Protein Profiling
11.2 Protein Chips
11.3 Reverse Phased Protein Microarrays
12 Emerging trends in Proteomics
12.1 Human Plasma Proteome
13 See also
13.1 Protein databases
13.2 Research centers
14 References
15 Bibliography
16 External links

Complexity of the problem

After genomics and transcriptomics, proteomics is the next step in the study of biological systems. It is more complicated than genomics because an organism’s genome is more or less constant, whereas the proteome differs from cell to cell and from time to time. Distinct genes are expressed in different cell types, which means that even the basic set of proteins that are produced in a cell needs to be identified.
In the past this phenomenon was done by mRNA analysis, but it was found not to correlate with protein content.[6][7] It is now known that mRNA is not always translated into protein,[8] and the amount of protein produced for a given amount of mRNA depends on the gene it is transcribed from and on the current physiological state of the cell. Proteomics confirms the presence of the protein and provides a direct measure of the quantity present.

Post-translational modifications
Not only does the translation from mRNA cause differences, but many proteins are also subjected to a wide variety of chemical modifications after translation. Many of these post-translational modifications are critical to the protein’s function.

Phosphorylation
One such modification is phosphorylation, which happens to many enzymes and structural proteins in the process of cell signaling. The addition of a phosphate to particular amino acids—most commonly serine and threonine[9] mediated by serine/threonine kinases, or more rarely tyrosine mediated by tyrosine kinases—causes a protein to become a target for binding or interacting with a distinct set of other proteins that recognize the phosphorylated domain.
Because protein phosphorylation is one of the most-studied protein modifications, many “proteomic” efforts are geared to determining the set of phosphorylated proteins in a particular cell or tissue-type under particular circumstances. This alerts the scientist to the signaling pathways that may be active in that instance.

Ubiquitination
Ubiquitin is a small protein that can be affixed to certain protein substrates by enzymes called E3 ubiquitin ligases. Determining which proteins are poly-ubiquitinated helps understand how protein pathways are regulated. This is, therefore, an additional legitimate “proteomic” study. Similarly, once a researcher determines which substrates are ubiquitinated by each ligase, determining the set of ligases expressed in a particular cell type is helpful.
Additional modifications[edit]
Listing all the protein modifications that might be studied in a “proteomics” project would require a discussion of most of biochemistry. Therefore, a short list illustrates the complexity of the problem. In addition to phosphorylation and ubiquitination, proteins can be subjected to (among others) methylation, acetylation, glycosylation, oxidation and nitrosylation. Some proteins undergo all these modifications, often in time-dependent combinations. This illustrates the potential complexity of studying protein structure and function.

(TEXT OMITTED)

Practical applications of proteomics

One major development to come from the study of human genes and proteins has been the identification of potential new drugs for the treatment of disease. This relies on genome and proteome information to identify proteins associated with a disease, which computer software can then use as targets for new drugs. For example, if a certain protein is implicated in a disease, its 3D structure provides the information to design drugs to interfere with the action of the protein. A molecule that fits the active site of an enzyme, but cannot be released by the enzyme, inactivates the enzyme. This is the basis of new drug-discovery tools, which aim to find new drugs to inactivate proteins involved in disease. As genetic differences among individuals are found, researchers expect to use these techniques to develop personalized drugs that are more effective for the individual.[19]
Proteomics is also used to reveal complex plant-insect interactions that help identify candidate genes involved in the defensive response of plants to herbivory.[20][21][

(TEXT OMITTED)

Proteomics and System Biology

Proteomics has recently come into the act as a promising force to transform biology and medicine. It is becoming increasingly apparent that changes in mRNA expression correlate poorly with protein expression changes. Proteins changes enormously in patterns of expressions across developmental and physiological responses. Proteins also face changes on the act of environmental perturbations. Proteins are the actual effectors driving cell behavior. The field of proteomics strives to characterize protein structure and function, protein-protein,protein-nucleic acid, protein-lipid, and enzyme-substrate interactions, protein processing and folding, protein activation, cellular and sub-cellular localization, protein turnover and synthesis rates, and even promoter usage. Integrating proteomic data with information such as gene, mRNA and metabolic profiles helps in better understanding of how the system works.[37]

(
See also[edit]

Activity based proteomics
Bioinformatics
Bottom-up proteomics
Cytomics
Functional genomics
Genomics
Heat stabilization
Immunomics
Immunoproteomics
Lipidomics
List of biological databases
List of omics topics in biology
Metabolomics
PEGylation
Phosphoproteomics
Proteogenomics
Proteomic chemistry
Secretomics
Shotgun proteomics
Top-down proteomics
Systems biology
Transcriptomics
Yeast two-hybrid system
Protein databases[edit]
Human Protein Atlas
Cardiac Organellar Protein Atlas Knowledgebase (COPaKB)
Human Protein Reference Database
Model Organism Protein Expression Database (MOPED)
National Center for Biotechnology Information (NCBI)
Protein Data Bank (PDB)
Protein Information Resource (PIR)
Proteomics Identifications Database (PRIDE)
Proteopedia The collaborative, 3D encyclopedia of proteins and other molecules
Swiss-Prot
UniProt
Research centers[edit]
European Bioinformatics Institute
Netherlands Proteomics Centre (NPC)
Proteomics Research Resource for Integrative Biology (NIH)
Global map of proteomics labs
References[edit]

Jump up^ Anderson NL, Anderson NG (1998). “Proteome and proteomics: new technologies, new concepts, and new words”.Electrophoresis 19 (11): 1853–61.doi:10.1002/elps.1150191103. PMID 9740045.
Jump up^ Blackstock WP, Weir MP (1999). “Proteomics: quantitative and physical mapping of cellular proteins”. Trends Biotechnol. 17 (3): 121–7. doi:10.1016/S0167-7799(98)01245-1.PMID 10189717.
Jump up^ P. James (1997). “Protein identification in the post-genome era: the rapid rise of proteomics”. Quarterly reviews of biophysics 30 (4): 279–331.doi:10.1017/S0033583597003399. PMID 9634650.
^ Jump up to:a b Marc R. Wilkins, Christian Pasquali, Ron D. Appel, Keli Ou, Olivier Golaz, Jean-Charles Sanchez, Jun X. Yan, Andrew. A. Gooley, Graham Hughes, Ian Humphery-Smith, Keith L. Williams & Denis F. Hochstrasser (1996). “From Proteins to Proteomes: Large Scale Protein Identification by Two-Dimensional Electrophoresis and Arnino Acid Analysis”. Nature Biotechnology 14 (1): 61–65. doi:10.1038/nbt0196-61.PMID 9636313.
Jump up^ UNSW Staff Bio: Professor Marc Wilkins
Jump up^ Simon Rogers, Mark Girolami, Walter Kolch, Katrina M. Waters, Tao Liu, Brian Thrall and H. Steven Wiley (2008). “Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models”.Bioinformatics 24 (24): 2894–2900.doi:10.1093/bioinformatics/btn553. PMID 18974169.
Jump up^ Vikas Dhingraa, Mukta Gupta, Tracy Andacht and Zhen F. Fu (2005). “New frontiers in proteomics research: A perspective”.International Journal of Pharmaceutics 299 (1–2): 1–18.doi:10.1016/j.ijpharm.2005.04.010. PMID 15979831.
Jump up^ Buckingham, Steven (May 2003). “The major world of microRNAs”. Retrieved 2009-01-14.
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Jump up^ Gygi, S. P.; Rochon, Y.; Franza, B. R.; Aebersold, R. (1999).”Correlation between protein and mRNA abundance in yeast”.Molecular and Cellular Biology 19 (3): 1720–1730.PMC 83965. PMID 10022859. edit
Jump up^ Archana Belle, Amos Tanay, Ledion Bitincka, Ron Shamir and Erin K. O’Shea (2006). “Quantification of protein half-lives in the budding yeast proteome”. PNAS 103 (35): 13004–13009.Bibcode:2006PNAS..10313004B.doi:10.1073/pnas.0605420103. PMC 1550773.PMID 16916930.
Jump up^ Peng, J.; Elias, J. E.; Thoreen, C. C.; Licklider, L. J.; Gygi, S. P. (2003). “Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: The yeast proteome”. Journal of proteome research 2 (1): 43–50. PMID 12643542. edit
Jump up^ Washburn, M. P.; Wolters, D.; Yates, J. R. (2001). “Large-scale analysis of the yeast proteome by multidimensional protein identification technology”. Nature Biotechnology 19 (3): 242–247. doi:10.1038/85686. PMID 11231557. edit
^ Jump up to:a b c d Klopfleisch R, Klose P, Weise C, Bondzio A, Multhaup G, Einspanier R, Gruber AD. (2010). “Proteome of metastatic canine mammary carcinomas: similarities to and differences from human breast cancer”. J Proteome Res 9 (12): 6380–91.doi:10.1021/pr100671c. PMID 20932060.
Jump up^ Dix MM, Simon GM, Cravatt BF (August 2008). “Global mapping of the topography and magnitude of proteolytic events in apoptosis”. Cell 134 (4): 679–91.doi:10.1016/j.cell.2008.06.038. PMC 2597167.PMID 18724940.
Jump up^ Minde DP (2012). “Determining biophysical protein stability in lysates by a fast proteolysis assay, FASTpp”. PLOS ONE 7(10): e46147. Bibcode:2012PLoSO…746147M.doi:10.1371/journal.pone.0046147. PMC 3463568.PMID 23056252.
Jump up^ Maron JL, Alterovitz G, Ramoni M, Johnson KL, Bianchi DW (December 2009). “High-throughput discovery and characterization of fetal protein trafficking in the blood of pregnant women”. Proteomics Clin Appl 3 (12): 1389–96.doi:10.1002/prca.200900109. PMC 2825712.PMID 20186258.
Jump up^ Alterovitz G, Xiang M, Liu J, Chang A, Ramoni MF (2008).”System-wide peripheral biomarker discovery using information theory”. Pacific Symposium on Biocomputing: 231–42.PMID 18229689.
Jump up^ Vaidyanathan G (March 2012). “Redefining clinical trials: the age of personalized medicine”. Cell 148 (6): 1079–80.doi:10.1016/j.cell.2012.02.041. PMID 22424218.
Jump up^ Rakwal, Randeep; Komatsu, Setsuko (2000). “Role of jasmonate in the rice (Oryza sativa L.) self-defense mechanism using proteome analysis”. Electrophoresis 21 (12): 2492–500.doi:10.1002/1522-2683(20000701)21:12<2492::AID-ELPS2492>3.0.CO;2-2. PMID 10939463.
Jump up^ Wu, Jianqiang; Baldwin, Ian T. (2010). “New Insights into Plant Responses to the Attack from Insect Herbivores”. Annual Review of Genetics 44: 1–24. doi:10.1146/annurev-genet-102209-163500. PMID 20649414.
Jump up^ Sangha J.S., Chen Y.H., Kaur Jatinder, Khan Wajahatullah, Abduljaleel Zainularifeen, Alanazi Mohammed S., Mills Aaron, Adalla Candida B., Bennett John et al. (2013). “Proteome Analysis of Rice (Oryza sativa L.) Mutants Reveals Differentially Induced Proteins during Brown Planthopper (Nilaparvata lugens) Infestation”. Int. J. Mo Sci 14 (2): 3921–3945.doi:10.3390/ijms14023921. PMC 3588078.PMID 23434671.
Jump up^ Strimbu, Kyle; Tavel, Jorge A (2010). “What are biomarkers?”. Current Opinion in HIV and AIDS 5 (6): 463–6.doi:10.1097/COH.0b013e32833ed177. PMC 3078627.PMID 20978388.
Jump up^ Biomarkers Definitions Working Group (2001). “Biomarkers and surrogate endpoints: preferred definitions and conceptual framework”. Clinical Pharmacology & Therapeutics 69 (3): 89–95. doi:10.1067/mcp.2001.113989. PMID 11240971.
Jump up^ Klopfleisch R, Gruber AD (2009). “Increased expression of BRCA2 and RAD51 in lymph node metastases of canine mammary adenocarcinomas”. Veterinary Pathology 46 (3): 416–22. doi:10.1354/vp.08-VP-0212-K-FL. PMID 19176491.
Jump up^ Hathout, Yetrib (2007). “Approaches to the study of the cell secretome”. Expert Review of Proteomics 4 (2): 239–48.doi:10.1586/14789450.4.2.239. PMID 17425459.
Jump up^ Gupta N, Tanner S, Jaitly N, et al. (September 2007). “Whole proteome analysis of post-translational modifications: applications of mass-spectrometry for proteogenomic annotation”. Genome Res. 17 (9): 1362–77.doi:10.1101/gr.6427907. PMC 1950905.PMID 17690205.
Jump up^ Gupta N, Benhamida J, Bhargava V, et al. (July 2008).”Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes”.Genome Res. 18 (7): 1133–42. doi:10.1101/gr.074344.107.PMC 2493402. PMID 18426904.
^ Jump up to:a b Tonge R, Shaw J, Middleton B, et al. (March 2001). “Validation and development of fluorescence two-dimensional differential gel electrophoresis proteomics technology”.Proteomics 1 (3): 377–96. doi:10.1002/1615-9861(200103)1:3<377::AID-PROT377>3.0.CO;2-6.PMID 11680884.
Jump up^ Li-Ping Wang, Jun Shen, Lin-Quan Ge, Jin-Cai Wu, Guo-Qin Yang, Gary C. Jahn (November 2010). “Insecticide-induced increase in the protein content of male accessory glands and its effect on the fecundity of females in the brown planthopper,Nilaparvata lugens Stål (Hemiptera: Delphacidae)”. Crop Protection 29 (11): 1280–5. doi:10.1016/j.cropro.2010.07.009.
^ Jump up to:a b Ge, Lin-Quan; Cheng, Yao; Wu, Jin-Cai; Jahn, Gary C. (2011). “Proteomic Analysis of Insecticide Triazophos-Induced Mating-Responsive Proteins ofNilaparvata lugensStål (Hemiptera: Delphacidae)”. Journal of Proteome Research 10(10): 4597–612. doi:10.1021/pr200414g. PMID 21800909.
^ Jump up to:a b Reumann S (May 2011). “Toward a definition of the complete proteome of plant peroxisomes: Where experimental proteomics must be complemented by bioinformatics”.Proteomics 11 (9): 1764–79. doi:10.1002/pmic.201000681.PMID 21472859.
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Jump up^ Ole Nørregaard Jensen (2004). “Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry”. Current Opinion in Chemical Biology 8(1): 33–41. doi:10.1016/j.cbpa.2003.12.009.PMID 15036154.
Jump up^ Chandramouli, Kondethimmanahalli; Qian, Pei-Yuan (2009). “Proteomics: Challenges, Techniques and Possibilities to Overcome Biological Sample Complexity”. Human Genomics and Proteomics 2009: 1. doi:10.4061/2009/239204.
^ Jump up to:a b c d e f “What is Proteomics?”. ProteoConsult.[unreliable medical source?]
^ Jump up to:a b c d e f g Weston, Andrea D.; Hood, Leroy (2004). “Systems Biology, Proteomics, and the Future of Health Care: Toward Predictive, Preventative, and Personalized Medicine”. Journal of Proteome Research 3 (2): 179–96. doi:10.1021/pr0499693.PMID 15113093.
Bibliography[edit]

Belhajjame, K. et al. Proteome Data Integration: Characteristics and Challenges. Proceedings of the UK e-Science All Hands Meeting, ISBN 1-904425-53-4, September 2005, Nottingham, UK.
Twyman RM (2004). Principles Of Proteomics (Advanced Text Series). Oxford, UK: BIOS Scientific Publishers. ISBN 1-85996-273-4. (covers almost all branches of proteomics)
Naven T, Westermeier R (2002). Proteomics in Practice: A Laboratory Manual of Proteome Analysis. Weinheim: Wiley-VCH.ISBN 3-527-30354-5. (focused on 2D-gels, good on detail)
Liebler DC (2002). Introduction to proteomics: tools for the new biology. Totowa, NJ: Humana Press. ISBN 0-89603-992-7. ISBN 0-585-41879-9 (electronic, on Netlibrary?), ISBN 0-89603-991-9 hbk
Wilkins MR, Williams KL, Appel RD, Hochstrasser DF (1997).Proteome Research: New Frontiers in Functional Genomics (Principles and Practice). Berlin: Springer. ISBN 3-540-62753-7.
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Rediscovering Biology Online Textbook. Unit 2 Proteins and Proteomics. 1997–2006.
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External links[edit]

Proteomics on the Open Directory Project
http://www.merriam-webster.com/dictionary/proteomics.html
Look up proteomics in Wiktionary, the free dictionary.
Wikibooks has more on the topic of: Proteomics
At Wikiversity you can learn more and teach others aboutProteomics at:
The Department of Proteomics
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Personalized medicine
From Wikipedia, the free encyclopedia
Personalized medicine or PM is a medical model that proposes the customization of healthcare – with medical decisions, practices, and/or products being tailored to the individual patient. In this model, diagnostic testing is essential for selecting appropriate therapies; terms used to describe these tests include “”companion diagnostics”, “theranostics” (a portmanteau of therapeutics and diagnostics), and “therapygenetics”. The use of genetic information has played a major role in certain aspects of personalized medicine, and the term was even first coined in the context of genetics (though it has since broadened to encompass all sorts of personalization measures). To distinguish from the sense in which medicine has always been inherently “personal” to each patient, PM commonly denotes the use of some kind of technology or discovery enabling a level of personalization not previously feasible or practical.
Contents [hide]
1 Background
2 Technologies
3 Examples
3.1 Cancer management
4 Psychiatry and psychological therapy
5 See also
6 References
7 Further reading
8 External links
Background[edit]

Traditional clinical diagnosis and management focuses on the individual patient’s clinical signs and symptoms, medical and family history, and data from laboratory and imaging evaluation to diagnose and treat illnesses. This is often a reactive approach to treatment, i.e., treatment/medication starts after the signs and symptoms appear.
Advances in medical genetics and human genetics have enabled a more detailed understanding of the impact of genetics in disease. Large collaborative research projects (for example, the Human genome project) have laid the groundwork for the understanding of the roles of genes in normal human development and physiology, revealed single nucleotide polymorphisms (SNPs) that account for some of the genetic variability between individuals, and made possible the use of genome-wide association studies (GWAS) to examine genetic variation and risk for many common diseases.
Historically, the pharmaceutical industry has developed medications based on empiric observations and more recently, known disease mechanisms.[citation needed] For example, antibiotics were based on the observation that microbes produce substances that inhibit other species. Agents that lower blood pressure have typically been designed to act on certain pathways involved in hypertension(such as renal salt and water absorption, vascular contractility, and cardiac output). Medications for high cholesterol target the absorption, metabolism, and generation of cholesterol. Treatments for diabetes are aimed at improving insulin release from the pancreas and sensitivity of the muscle and fat tissues to insulin action. Thus, medications are developed based on mechanisms of disease that have been extensively studied over the past century. It is hoped that recent advancements in the genetic etiologies of common diseases will improve pharmaceutical development.
Technologies[edit]

Since the late 1990s, the advent of research using biobanks has brought advances in molecular biology, proteomics, metabolomicanalysis, genetic testing, and molecular medicine. Another significant development has been the notion of companion diagnostics, whereby molecular assays that measure levels of proteins, genes, or specific mutations are used to provide a specific therapy for an individual’s condition – by stratifying disease status, selecting the proper medication, and tailoring dosages to that patient’s specific needs. Additionally, such methods might be used to assess a patient’s risk factor for a number of conditions and tailor individualpreventative treatments.
Pharmacogenetics (also termed pharmacogenomics) is the field of study that examines the impact of genetic variation and responses to therapeutic interventions by biomarker (medicine).[1] This approach is aimed at tailoring drug therapy at a dosage that is most appropriate for an individual patient, with the potential benefits of increasing the efficacy and safety of medications.[2] Other benefits include reduced time, cost, and failure rates of clinical trials in the production of new drugs by using precise biomarkers.[3] Gene-centered research may also speed the development of novel therapeutics.[4]
The field of proteomics, or the comprehensive analysis and characterization of all of the proteins and protein isoforms encoded by thehuman genome, may eventually have a significant impact on medicine. This is because while the DNA genome[5] is the information archive, it is the proteins that do the work of the cell: the functional aspects of the cell are controlled by and through proteins, not genes.
It has also been demonstrated that pre-dose metabolic profiles from urine can be used to predict drug metabolism.[6][7]Pharmacometabolomics refers to the direct measurement of metabolites in an individual’s bodily fluids, in order to predict or evaluate the metabolism of pharmaceutical compounds.
Examples[edit]

Some examples of personalized medicine include:
Genotyping for SNPs in genes involved in the action and metabolism of warfarin (Coumadin). This medication is used clinically as an anticoagulant but requires periodic monitoring and is associated with adverse side affects. Recently, genetic variants in the gene encoding Cytochrome P450 enzyme CYP2C9, which metabolizes warfarin,[8] and the Vitamin K epoxide reductase gene (VKORC1), a target of coumarins,[9] have led to commercially-available testing that enables more accurate dosing based on algorithms that take into account the age, gender, weight, and genotype of an individual.
Genotyping variants in genes encoding Cytochrome P450 enzymes (CYP2D6, CYP2C19, and CYP2C9), which metabolize neuroleptic medications, to improve drug response and reduce side-effects.[10]
Cancer management[edit]
Oncology is a field of medicine with a long history of classifying tumor stages and subtypes based on anatomic and pathologic findings. This approach includes histological examination of tumor specimens from individual patients (such as HER2/NEU in breast cancer) to look for markers associated with prognosis and likely treatment responses. Thus, “personalized medicine” was in practice long before the term was coined. New molecular testing methods have enabled an extension of this approach to include testing for global gene, protein, and protein pathway activation expression profiles and/or somatic mutations in cancer cells from patients in order to better define the prognosis in these patients and to suggest treatment options that are most likely to succeed.[11][12]
Examples of personalized cancer management include:
Companion diagnostics for targeted therapies.
Trastuzumab (trade names Herclon, Herceptin) is a monoclonal antibody drug that interferes with the HER2/neu receptor. Its main use is to treat certain breast cancers. This drug is only used if a patient’s cancer is tested for overexpression the HER2/neu receptor. Two of the most common tests used are the (Dako) HercepTest and Genentech’s Herceptin.[13] Only Her2+ patients will be treated with Herceptin therapy (trastuzumab)[14]
Tyrosine kinase inhibitors such as imatinib (marketed as Gleevec) have been developed to treat chronic myeloid leukemia(CML), in which the BCR-ABL fusion gene (the product of a reciprocal translocation between chromosome 9 and chromosome 22) is present in >95% of cases and produces hyperactivated abl-driven protein signaling. These medications specifically inhibit the Ableson tyrosine kinase (ABL) protein and are thus a prime example of “rational drug design” based on knowledge of disease pathophysiology.[15]
Testing for disease-causing mutations in the BRCA1 and BRCA2 genes, which are implicated in hereditary breast–ovarian cancer syndromes. Discovery of a disease-causing mutation in a family can inform “at-risk” individuals as to whether they are at higher risk for cancer and may prompt individualized prophylactic therapy including mastectomy and removal of the ovaries. This testing involves complicated personal decisions and is undertaken in the context of detailed genetic counseling. More detailed molecular stratification of breast tumors may pave the way for future tailored treatments.[16] These tests are part of the emerging field ofcancer genetics, which is a specialized field of medical genetics concerned with hereditary cancer risk.
Psychiatry and psychological therapy[edit]

Efforts are underway to apply the tools of personalized medicine to psychiatry and psychological therapy; these technologies are still under development as of 2013.
In 2012 Professor Thalia Eley and her research team coined the term “therapygenetics” refers to a branch of psychiatric genetic research looking at the relationship between specific genetic variants and differences in the level of success of psychological therapy.[17][18] The field is parallel to pharmacogenetics, which explores the association between specific genetic variants and the efficacy of drug treatments. Therapygenetics work also relates to the differential susceptibility hypothesis [19] which proposes that individuals have a genetic predisposition to respond to a greater or lesser extent to their environment, be it positive or negative.
See also[edit]

Predictive medicine
Whole genome sequencing
Drug development
Translational Research
$1,000 genome
References[edit]

Jump up^ Shastry BS (2006). “Pharmacogenetics and the concept of individualized medicine”. Pharmacogenomics J. 6 (1): 16–21.doi:10.1038/sj.tpj.6500338. PMID 16302022.
Jump up^ Ozdemir, Vural; Williams-Jones, Bryn; Glatt, Stephen J; Tsuang, Ming T; Lohr, James B; Reist, Christopher (August 2006). “Shifting emphasis from pharmacogenomics to theranostics”. Nature Biotechnology 24 (8): 942–946. Retrieved 30 March 2013.
Jump up^ Galas, D. J., & Hood, L. (2009). “Systems Biology and Emerging Technologies Will Catalyze the Transition from Reactive Medicine to Predictive, Personalized, Preventive and Participatory (P4) Medicine”. Interdisciplinary Bio Central 1: 1–4.doi:10.4051/ibc.2009.2.0006.
Jump up^ Shastry BS (2006). “Pharmacogenetics and the concept of individualized medicine”. Pharmacogenomics J. 6 (1): 16–21.doi:10.1038/sj.tpj.6500338. PMID 16302022.
Jump up^ Harmon, Katherine (2010-06-28). “Genome Sequencing for the Rest of Us”. Scientific American. Retrieved 2010-08-13.
Jump up^ Clayton TA, Lindon JC, Cloarec O, et al. (April 2006). “Pharmaco-metabonomic phenotyping and personalized drug treatment”. Nature 440 (7087): 1073–7.doi:10.1038/nature04648. PMID 16625200.
Jump up^ Clayton TA, Baker D, Lindon JC, Everett JR, Nicholson JK (August 2009). “Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism”. Proc. Natl. Acad. Sci. U.S.A. 106(34): 14728–33. doi:10.1073/pnas.0904489106.PMC 2731842. PMID 19667173.
Jump up^ Schwarz UI (November 2003). “Clinical relevance of genetic polymorphisms in the human CYP2C9 gene”. Eur. J. Clin. Invest. 33. Suppl 2: 23–30. doi:10.1046/j.1365-2362.33.s2.6.x. PMID 14641553.
Jump up^ Oldenburg J, Watzka M, Rost S, Müller CR (July 2007). “VKORC1: molecular target of coumarins”. J. Thromb. Haemost. 5. Suppl 1: 1–6. doi:10.1111/j.1538-7836.2007.02549.x.PMID 17635701.
Jump up^ Cichon S, Nöthen MM, Rietschel M, Propping P (2000). “Pharmacogenetics of schizophrenia”. Am. J. Med. Genet. 97(1): 98–106. doi:10.1002/(SICI)1096-8628(200021)97:1<98::AID-AJMG12>3.0.CO;2-W.PMID 10813809.
Jump up^ Mansour JC, Schwarz RE (August 2008). “Molecular mechanisms for individualized cancer care”. J. Am. Coll. Surg.207 (2): 250–8. doi:10.1016/j.jamcollsurg.2008.03.003.PMID 18656055.
Jump up^ van’t Veer LJ, Bernards R (April 2008). “Enabling personalized cancer medicine through analysis of gene-expression patterns”.Nature 452 (7187): 564–70. doi:10.1038/nature06915.PMID 18385730.
Jump up^ Carney, Walter (2006). “HER2/neu Status is an Important Biomarker in Guiding Personalized HER2/neu Therapy”.Connection 9: 25–27.
Jump up^ Telli, M. L.; Hunt, S. A.; Carlson, R. W.; Guardino, A. E. (2007). “Trastuzumab-Related Cardiotoxicity: Calling Into Question the Concept of Reversibility”. Journal of Clinical Oncology 25 (23): 3525–3533.doi:10.1200/JCO.2007.11.0106. ISSN 0732-183X.PMID 17687157.
Jump up^ Saglio G, Morotti A, Mattioli G, et al. (December 2004). “Rational approaches to the design of therapeutics targeting molecular markers: the case of chronic myelogenous leukemia”.Ann. N. Y. Acad. Sci. 1028 (1): 423–31.doi:10.1196/annals.1322.050. PMID 15650267.
Jump up^ Gallagher, James (19 April 2012). “Breast cancer rules rewritten in ‘landmark’ study”. BBC News. Retrieved 19 April 2012.
Jump up^ Lester, KJ; Eley TC (2013). “Therapygenetics: Using genetic markers to predict response to psychological treatment for mood and anxiety disorders”. Biology of mood & anxiety disorders 3(1): 1–16. doi:10.1186/2045-5380-3-4. PMC 3575379.PMID 23388219.
Jump up^ Beevers, CG; McGeary JE (2012). “Therapygenetics: moving towards personalized psychotherapy treatment”. Trends in Cognitive Sciences 16 (1): 11–12.doi:10.1016/j.tics.2011.11.004. PMC 3253222.PMID 22104133.
Jump up^ Belsky J, Jonassaint C, Pluess M, Stanton M, Brummett B, Williams R (August 2009). “Vulnerability genes or plasticity genes?”. Mol. Psychiatry 14 (8): 746–54.doi:10.1038/mp.2009.44. PMC 2834322.PMID 19455150.
Further reading[edit]

Daskalaki A, Wierling C, Herwig R (2009), Computational tools and resources for systems biology approaches in cancer.In Computational Biology – Issues and Applications in Oncology, Series: Applied Bioinformatics and Biostatistics in Cancer Research, Pham, Tuan (Ed.), Springer, New York Dordrecht Heidelberg London. 2009:227-242.
Acharya et al. (2008), Gene Expression Signatures, clinicopathological features, and individualized therapy in breast cancer, JAMA 299: 1574.
Sadee W, Dai Z. (2005), Pharmacogenetics/genomics and personalized medicine, Hum Mol Genet. 2005 October 15;14 Spec No. 2:R207-14.
Steven H. Y. Wong (2006), Pharmacogenomics and Proteomics: Enabling the Practice of Personalized Medicine, American Association for Clinical Chemistry, ISBN 1-59425-046-4
Qing Yan (2008), Pharmacogenomics in Drug Discovery and Development, Humana Press, 2008, ISBN 1-58829-887-6.
Willard, H.W., and Ginsburg, G.S., (eds), (2009), Genomic and Personalized Medicine, Academic Press, 2009, ISBN 0-12-369420-5.
Haile, Lisa A. (2008), Making Personalized Medicine a Reality, Genetic Engineering & Biotechnology News Vol. 28, No. 1.
Hornberger J, Habraken H, Bloch DA. Minimum data needed on patient preferences for accurate, efficient medical decision making. Medical Care 1995; 33:297-310.
Lyman GH, Cosler LE, Kuderer NM, Hornberger J. Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies. Cancer 2007; 109(6):1011-8.
Hornberger J, Cosler L and Lyman G. Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node–negative, estrogen-receptor–positive, early-stage breast cancer. Am J Managed Care 2005; 11:313-24.
A.Daskalaki & A.Lazakidou (2011). Quality Assurance in Healthcare Service Delivery, Nursing and Personalized Medicine: Technologies and Processes. IGI Global. ISBN 978-1-61350-120-7
Picard FJ, Bergeron MG., Rapid molecular theranostics in infectious diseases, Drug Discov Today. 2002 Nov 1;7(21):1092-101.
Hooper JW., The genetic map to theranostics, MLO Med Lab Obs. 2006 Jun;38(6):22-3, 25.
External links[edit]

CancerDriver : a free and open database to promote personalized medicine in oncology.
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Personal genomics
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Medicine
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Emerging technologies
Categories: Evidence-based medicineGeneticsGenomicsHealth informaticsMonoclonal antibodiesPharmacologyEmerging technologies

History of Computing


Www.computerhistory.org/timeline/

See also 2001 and 2007 posts (this is a more extensive more current update):

And