For decades the amyloid hypothesis has dominated the research field in Alzheimer’s disease. The theory describes how an increase in secreted beta-amyloid peptides leads to the formation of plaques, toxic clusters of damaged proteins between cells, which eventually result in neurodegeneration. Scientists at Lund University, Sweden, have now presented a study that turns this premise on its head. The research group’s data offers an opposite hypothesis, suggesting that it is in fact the neurons’ inability to secrete beta-amyloid that is at the heart of pathogenesis in Alzheimer’s disease.

The study, published in the October issue of the Journal of Neuroscience, shows an increase in unwanted intracellular beta-amyloid occurring early on in Alzheimer’s disease. The accumulation of beta-amyloid inside the neuron is here shown to be caused by the loss of normal function to secrete beta-amyloid.

Contrary to the dominant theory, where aggregated extracellular beta-amyloid is considered the main culprit, the study instead demonstrates that reduced secretion of beta-amyloid signals the beginning of the disease.

The damage to the neuron, created by the aggregated toxic beta-amyloid inside the cell, is believed to be a prior step to the formation of plaques, the long-time hallmark biomarker of the disease.

Professor Gunnar Gouras, the senior researcher of the study, hopes that the surprising new findings can help push the research field in a new direction.

“The many investigators and pharmaceutical companies screening for compounds that reduce secreted beta-amyloid have it the wrong way around. The problem is rather the opposite, that it is not getting secreted. To find the root of the disease, we now need to focus on this critical intracellular pool of beta-amyloid.

“We are showing here that the increase of intracellular beta-amyloid is one of the earliest events occurring in Alzheimer’s disease, before the formation of plaques. Our experiments clearly show a decreased secretion of beta-amyloid in our primary neuron disease model. This is probably because the cell’s metabolism and secretion pathways are disrupted in some way, leading beta-amyloid to be accumulated inside the cell instead of being secreted naturally,” says Davide Tampellini, first author of the study.

The theory of early accumulation of beta-amyloid inside the cell offers an alternate explanation for the formation of plaques. When excess amounts of beta-amyloid start to build up inside the cell, it is also stored in synapses. When the synapses can no longer hold the increasing amounts of the toxic peptide the membrane breaks, releasing the waste into the extracellular space. The toxins released now create the seed for other amyloids to gather and start forming the plaques.

The above story is reprinted from materials provided by Lund University.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

1. D. Tampellini, N. Rahman, M. T. Lin, E. Capetillo-Zarate, G. K. Gouras. Impaired  -Amyloid Secretion in Alzheimer’s Disease Pathogenesis. Journal of Neuroscience, 2011; 31 (43): 15384 DOI: 10.1523/JNEUROSCI.2986-11.2011

Obstructive sleep apnea may cause changes in blood vessel function that reduces blood supply to the heart in people who are otherwise healthy, according to new research reported in Hypertension: Journal of the American Heart Association. However, treatment with 26 weeks of continuous positive airway pressure (CPAP) improved study participants’ blood supply and function.

Obstructive sleep apnea, which causes periodic pauses in breathing during sleep, affects about 15 million adults in the United States, according to the American Heart Association. The sleep disorder may be a contributing factor to high blood pressure and cardiovascular diseases.

“The findings should change how doctors treat patients with obstructive sleep apnea,” said Gregory Y.H. Lip, M.D., lead author of the study and professor of cardiovascular medicine at the University of Birmingham in the United Kingdom. “Even apparently healthy patients with sleep apnea show abnormalities of small and large blood vessels, as well as impaired blood supply to the heart muscle, and these can improve with CPAP therapy.”

CPAP treatment provides a constant airflow that holds the airway open to maintain uninterrupted breathing during sleep. This eliminates sleep apnea events and allows the patient to get a restful sleep.

The study is the first to show blood vessel abnormalities in sleep apena patients. Previous studies have linked blood vessel dysfunction to cardiovascular disorders.

Reversing blood vessel abnormalities could help patients with obstructive sleep apnea who are otherwise healthy avoid developing and dying from cardiovascular disorders, researchers said.

Researchers looked for changes in blood vessel function in 108 participants who were otherwise healthy, with no differences in age, sex, body mass index and smoking status across three groups:

• 36 people with moderate or severe obstructive sleep apnea without high blood pressure
• 36 high blood pressure patients without obstructive sleep apnea
• 36 patients with neither high blood pressure nor obstructive sleep apnea

Researchers used several techniques to assess blood vessel function, including myocardial contrast echocardiography to check the blood supply to the heart muscle.

All the sleep apnea patients received CPAP therapy; so proper randomized studies will still be needed to confirm the intervention’s beneficial effects on the blood vessels, Lip said.

Furthermore, patients in the control groups weren’t treated with CPAP therapy, which would have been clinically unjustified because none had obstructive sleep apnea, researchers said.

Lip hopes his research will bring greater awareness to the relationship between obstructive sleep apnea and cardiovascular diseases. “The condition can be treated, and it is important that clinicians look out for it,” he said.

Co-authors of the study are: Mehmood Butt, M.D., M.B.B.S; Omer A. Khair, Ph.D.; Girish Dwivedi, M.D.; Alena Shantsila, M.D.; and Eduard Shantsila, M.D.

Periodontal disease is a chronic inflammatory disorder that causes gum tissues to pull away from the teeth, allowing bacteria to accumulate and trigger an inflammatory reaction that leads to the loss of bone tissues and teeth. In addition to the misery associated with the loss of one’s teeth, new research shows a positive link between the onset of periodontal disease and other chronic inflammatory disorders, including diabetes, cardiovascular disease, prostatitis and rheumatoid arthritis.

Periodontitis occurs when bacteria gather and form a “biofilm” that coats tooth surfaces at or below the gum line. These bacteria emit toxins that cause the body to mount an inflammatory response that, in turn, begins to eat away at gum tissues, leading to gingivitis. Eventually, if the source of inflammation is not brought under control, the process can result in the destruction of supportive bone structures (alveolar bone) that play a critical role in anchoring teeth firmly in place. As these retaining tissues break down, once-firm teeth become loose, leading to increasing inflammation, loss of bone and eventually requiring extraction.

Inflamed, bleeding gums and the loss of teeth, however, are only a part of the potential damage arising from periodontal disease. Gum disease is essentially an open wound that allows bacteria and their toxins to enter the body and cause widespread damage. Research has established that advanced periodontal disease contributes to atherosclerosis, heart attack, stroke and diabetes. Conversely, diabetes, osteoporosis and osteoarthritis have been shown to contribute to periodontal disease.

Gum Health and Periodontitis
While periodontitis is recognized as the most common form of chronic infection and inflammation in humans, the number of people in the United States afflicted with periodontitis turns out to be significantly higher than was originally believed. In a recent National Health and Nutrition Examination Survey (NHANES) study, a full-mouth, comprehensive periodontal examination of over 450 adults over the age of 35 was compared with the results of earlier studies that relied on only a partial-mouth periodontal examination. The recent study shows that the previous partial-mouth study methodology may have underestimated the true incidence of periodontal disease by up to 50 percent.(1)

According to Samuel Low, DDS, MS, president of the American Academy of Periodontology, “This study shows that periodontal disease is a bigger problem than we all thought. It is a call to action for anyone who cares about his or her oral health. Given what we know about the relationship between gum disease and other diseases, taking care of your oral health isn’t just about a pretty smile. It has bigger implications for overall health, and is therefore a more significant public health problem.”

How ‘Jailbreaking’ Bacteria can Trigger Heart Disease
A growing body of research now links gum disease with the onset of heart disease, caused when plaque-causing bacteria from the mouth enter into the bloodstream and increase the risk of heart attack. According to Professor Howard Jenkinson of the University of Bristol, England, oral bacteria can wreak havoc if they are not kept in check by regular brushing and flossing. “Poor dental hygiene can lead to bleeding gums, providing bacteria with an escape route into the bloodstream, where they can initiate blood clots leading to heart disease,” he said.(2)

Streptococcus bacteria commonly live in the mouth, confined within communities termed “biofilms” that are responsible for causing tooth plaque and gum disease. Researchers have now shown that once let loose in the bloodstream, Streptococcus bacteria can use a protein, called PadA, as a weapon to force platelets in the blood to bind together and form clots.

Inducing blood clots is a selfish trick used by bacteria, Jenkinson points out. “When the platelets clump together they completely encase the bacteria. This provides a protective cover not only from the immune system, but also from antibiotics that might be used to treat infection,” he said. “Unfortunately, as well as helping out the bacteria, platelet clumping can cause small blood clots, growths on the heart valves (endocarditis), or inflammation of blood vessels that can block the blood supply to the heart and brain.”

Professor Jenkinson said the research highlights a very important public health message. “People need to be aware that as well as keeping a check on their diet, blood pressure, cholesterol and fitness levels, they also need to maintain good dental hygiene to minimize their risk of heart problems.”

Periodontal Disease Linked to Prostatitis
In addition to contributing to development of heart disease, researchers from Case Western Reserve University School of Dental Medicine recently reported that initial results from a small sample shows that inflammation from gum disease and prostate problems just might be linked. In their paper, published in the official journal of the American Academy of Periodontology, the researchers described how they compared two unique markers for inflammation: Prostate-Specific Antigen (PSA), which is widely used to measure inflammation levels in prostate disease, and Clinical Attachment Level (CAL) of the gums and teeth, an indicator of periodontitis.

A PSA blood level of 4.0 ng/ml in the blood can be a sign of inflammation or malignancy, and patients with healthy prostate glands have lower than 4.0 ng/ml levels. A CAL number greater than 2.7 mm indicates periodontitis.

Like periodontitis, prostatitis also produces high inflammation levels. “Subjects with both high CAL levels and moderate to severe prostatitis have higher levels of PSA or inflammation,” stated Nabil Bissada, chair of the department of periodontics in the dental school. Bissada added that this might explain why PSA levels can be high in prostatitis, but sometimes cannot be explained by what is happening in the prostate glands. “It is something outside the prostate gland that is causing an inflammatory reaction,” he said. Because periodontitis has been linked to heart disease, diabetes and rheumatoid arthritis, the researchers felt a link might exist to prostate disease.

Thirty-five men from a sample of 150 patients qualified for their study, funded by the department of periodontology at the dental school. The participants were selected from patients with mild to severe prostatitis, who had undergone needle biopsies and were found to have inflammation and in some patients, malignancies.

The participants were divided into two groups: those with high PSA levels for moderate or severe prostatitis or a malignancy, and those with PSA levels below 4 ng/ml. All had not had dental work done for at least three months and were given an examination to measure the gum health. Looking at the results, the researchers from the dental school and the department of urology and the Institute of Pathology at the hospital found those with the most severe form of the prostatitis also showed signs for periodontitis.(3)

Polyunsaturated Fatty Acids may Reduce Periodontitis
In an article in the November issue of the Journal of the American Dietetic Association, researchers from Harvard Medical School and Harvard School of Public Health report that dietary intake of polyunsaturated fatty acids (PUFAs) like fish oil, known to have anti-inflammatory properties, shows promise for the effective treatment and prevention of periodontitis.

In a study involving over 9,000 adults, researchers found that omega-3 fatty acid intake, particularly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), were associated with reduced incidence of periodontitis. One of the study authors, Asghar Z. Naqvi commented, “To date, the treatment of periodontitis has primarily involved mechanical cleaning and local antibiotic application. Thus, a dietary therapy, if effective, might be a less expensive and safer method for the prevention and treatment of periodontitis. Given the evidence indicating a role for omega-3 fatty acids in other chronic inflammatory conditions, it is possible that treating periodontitis with omega-3 fatty acids could have the added benefit of preventing other chronic diseases associated with inflammation, including stroke as well.”

In their paper, the researchers reported an approximately 20 percent reduction in incidence of periodontitis in those consuming the highest amount of dietary DHA. The reduction correlated with EPA was smaller, while the correlation to LNA was not statistically significant. Foods that contain significant amounts of polyunsaturated fats include fatty fish like salmon, peanut butter and nuts.(4)

Summary
Given the increasing prevalence of periodontal disease and the growing body of research connecting periodontal health and systemic health, it is clearly essential to take steps to maintain healthy teeth and gums. According to Dr. Low, “Not only should you take good care of your periodontal health with daily tooth brushing and flossing, you should expect to get a comprehensive periodontal evaluation every year,” he advised. A dental professional, such as a periodontist, a specialist in the diagnosis, treatment and prevention of gum disease, will conduct the comprehensive exam to assess your periodontal disease status.

References
1. P. I. Eke, G. O. Thornton-Evans, L. Wei, W. S. Borgnakke, B. A. Dye. Accuracy of NHANES Periodontal Examination Protocols. Journal of Dental Research, 2010.
2. Society for General Microbiology (2010, September 5). ‘Jailbreak’ bacteria can trigger heart disease.
3. Joshi et al. Association Between Periodontal Disease and Prostate Specific Antigen Levels in Chronic Prostatitis Patients. Journal of Periodontology, 2010.
4. Asghar Z. Naqvi, Catherine Buettner, Russell S. Phillips, Roger B. Davis, Kenneth J. Mukamal. n-3 Fatty Acids and Periodontitis in US Adults. Journal of the American Dietetic Association, 2010; 110.

Jim English

With all the attention focused on the twin epidemics of obesity and Type 2 diabetes, few people are aware of another closely related condition that is rapidly becoming another major epidemic. According to the American Liver Association, fatty liver disease – marked by the abnormal accumulation of fat in the liver – currently affects as many as one in five Americans. Accompanied by a host of metabolic problems, including insulin resistance and increased serum triglycerides, fatty liver disease is often referred to as a “silent” disease because it rarely presents any noticeable symptoms.1

An estimated 30 percent of those with fatty liver disease will develop a much more serious disorder, Non-Alcoholic Steatohepatitis (NASH) that causes widespread inflammation and scarring (fibrosis) of liver tissues. People with NASH generally feel fine and are unaware they have a serious problem until the condition worsens and turns into cirrhosis. Cirrhosis is essentially widespread and extensive fibrosis that so severely damages the liver that it can no longer work, resulting in liver failure. Symptoms of cirrhosis include fluid retention, muscle wasting and bleeding from the intestines.

Liver transplantation is the only treatment for liver failure resulting from advanced cirrhosis, and transplants are increasingly being performed in people with NASH. NASH ranks as one of the major causes of cirrhosis in America, behind hepatitis C and alcoholic liver disease. Cirrhosis kills some 27,000 Ameri-cans per year.2

New Insights on Fatty Liver
A recent paper by nutrition researchers at the Washington University School of Medicine in St. Louis warns that fatty liver poses a far greater risk to health than normal belly fat, noting that “…excess fat in the liver, not visceral fat, is a key marker of metabolic dysfunction. Visceral fat might simply be an innocent bystander that is associated with liver fat.”3

According to senior investigator, Samuel Klein, M.D., “Since obesity is so much more common now, both in adults and in children, we are seeing a corresponding increase in the incidence of nonalcoholic fatty liver disease that can lead to serious liver disorders such as cirrhosis in extreme cases, but more often tends to have metabolic consequences. Multiple organ systems become resistant to insulin in these adolescent children with fatty liver disease. The liver becomes resistant to insulin and muscle tissue does, too. This tells us fat in the liver is a marker for metabolic problems throughout the entire system.”

According to Klein, their findings indicate that children and adults with fatty liver disease should be targeted for intensive interventions. “Those who are obese but don’t have fatty liver disease still should be encouraged to lose weight, but those with evidence of fatty liver are at particularly high risk for heart disease and diabetes. They need to be treated aggressively with therapies to help them lose weight because weight loss can make a big difference.”

Curcumin (Curcuma longa)
Curcumin (Curcuma longa) is a traditional herb that is rich in antioxidant polyphenolic compounds that have been shown to protect cells from free radical damage. Curcumin has previously been shown to prevent obesity-associated inflammation and diabetes (Fig. 1) in obese mice. In one recent study curcumin was found to inhibit lipogenesis (the process by which glucose is converted to fat) and prevent the development of new fat cells.4

Fig. 1. Progressive weight gain leads to adipocyte enlargement and a proinflammatory state with increased macrophage activation, secretion of chemokines and cytokines, and endothelial damage.

In a recent paper, curcumin was shown to suppress cellular expression of GLUT4 (Insulin-Responsive Glucose Transporter), a protein found in striated muscles and adipose tissues that is responsible for the insulin-regulated transfer of glucose into cells where it is either metabolized for energy or stored as fat. By suppressing GLUT4 expression, curcumin acts to inhibit lipogenesis and suppress the formation of new fat cells. Additionally, by decreasing GLUT4, curcumin increases lipolysis, the process by which triglycerides (which make up the bulk of fat cells) are converted into free fatty acids that can easily be metabolized (burned as fuel) leading to a reduction in fat storage and causing adipose cells to shrink.5

How Curcumin Enhances Fat Loss
In 2009, researchers at Tufts University examined how curcumin affects fat metabolism and storage. They discovered that when mice were fed a high-fat diet supplemented with curcumin, their intake of calories remained constant even as they lost body weight and adipose tissue. Curcumin also led to a reduction in the density of microcapillaries feeding fat cells, and a similar drop in the expression of vascular endothelial growth factor (VEGF), a chemical that stimulates the growth of new blood vessels.

Additionally, curcumin was found to significantly lower serum cholesterol levels in the mice while reducing expression of PPAR, a key transcription factor involved in fat cell formation and storage. Commenting on their findings, the researchers noted that, “The curcumin suppression of angiogenesis in adipose tissue, together with its effect on lipid metabolism in adipocytes, may contribute to reduced body fat and body weight gain. Our findings suggest that dietary curcumin may have a potential benefit in preventing obesity.”6

How Curcumin Protects Against Fatty Liver and NASH
Another team of researchers from the Washington University School of Medi-cine recently published a study showing how curcumin prevents the accumulation of fat in the liver by inhibiting leptin, a hormone produced by fat cells that plays a key role in regulating appetite and fat storage. Normally, leptin acts on receptors in the hypothalamus to limit appetite and produce a sense of fullness and satisfaction after eating a meal (satiety). Leptin also enhances the body’s ability to access and utilize stored fat for energy production.

But leptin also has a dark side. Leptin stimulates the activation of Hepatic Stellate Cells (HSCs), a class of liver cells directly involved in the development of nonalcoholic steatohepatitis (NASH), a condition associated with increased damage from reactive oxygen species (ROS), mitochondrial dysfunction, and inflammatory cyto-kines. Obese individuals are increasingly being diagnosed with NASH, presenting with symptoms that include abnormally high plasma leptin levels, fatty liver, inflammation and severe fibrosis of liver tissues.

In their paper, the researchers described how curcumin was found to block the damaging stimulatory effects of leptin on HSC activation while also increasing activity of AMPK (AMP-activated protein kinase), a master switch that regulates several intracellular systems, including fatty acid and carbohydrate metabolism in liver, adipose tissue, pancreatic cells, and skeletal muscles.

Summary
Curcumin has been shown to reduce the damaging effects of leptin on Hepatic Stellate Cells while reducing oxidative stress to further inhibit leptin-signaling. These results provide a novel insight into potential therapeutic application of curcumin for preventing liver fibrogenesis associated with fatty liver disease and NASH.

References
1. US Dept. of Veterans Affairs; Fatty Liver Disease: A New Epidemic? VA Research Currents, June 2007.
2. National Digestive Diseases Information Clearing-house (NDDIC), a service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH Publication No. 07–4921, Nov. 2006.
3. Fabbrini E, Magkos F, Mohammed BS, et.al. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. Proc Natl Acad Sci U S A. 2009 Sep 8;106(36):15430-5. Epub 2009 Aug 24.
4. Ahn J, Lee H, Kim S, Ha T., Curcumin-induced suppression of adipogenic differentiation is accompanied by activation of Wnt/beta-catenin signaling. Am J Physiol Cell Physiol. 2010 Jun;298(6):C1510-6.
5. Lee J, Yoon HG, Lee YH, et.al. The potential effects of ethyl acetate fraction from Curcuma longa L. on lipolysis in differentiated 3T3-L1 adipocytes. J Med Food. 2010 Apr;13(2):364-70.
6. A. Ejaz, D. Wu, P. Kwan, M. Meydani. Curcumin Inhibits Adipogenesis in 3T3-L1 Adipocytes and Angiogenesis and Obesity in C57/BL Mice. Journal of Nutrition, Vol. 139, No. 5, 919-925, May 2009

The United States continues to lag behind other nations when it comes to gains in life expectancy, and commonly cited causes for our poor performance — obesity, smoking, traffic fatalities, and homicide — are not to blame, according to a Commonwealth Fund-supported study published as a Health Affairs Web First.

The study, by Peter Muennig and Sherry Glied at Columbia University, looked at health spending; behavioral risk factors like obesity and smoking; and 15-year survival rates for men and women ages 45 and 65 in the U.S. and 12 other nations (Australia, Austria, Belgium, Canada, France, Germany, Italy, Japan, the Netherlands, Sweden, Switzerland, and the United Kingdom).

While the U.S. has achieved gains in 15-year survival rates decade by decade between 1975 and 2005, the researchers discovered that other countries have experienced even greater gains, leading the U.S. to slip in country ranking, even as per capita health care spending in the U.S. increased at more than twice the rate of the comparison countries. Fifteen-year survival rates for men and women ages 45 and 65 in the US have fallen relative to the other 12 countries over the past 30 years. Forty-five year old U.S. white women fared the worst — by 2005 their 15-year survival rates were lower than that of all the other countries. Moreover, the survival rates of this group in 2005 had not even surpassed the 1975 15-year survival rates for Swiss, Swedish, Dutch or Japanese women. The U.S. ranking for 15-year life expectancy for 45-year-old men also declined, falling from 3rd in 1975 to 12th in 2005, according to the study, “What Changes in Survival Rates Tell Us About U.S. Health Care.”

When the researchers compared risk factors among the 13 countries, they found very little difference in smoking habits between the U.S. and the comparison countries — in fact, the U.S. had faster declines in smoking between 1975 and 2005 than almost all of the other countries. In terms of obesity, the researchers found that, while people in the U.S. are more likely to be obese, this was also the case in 1975, when the U.S. was not so far behind in life expectancy. In fact, even as the comparison countries pulled ahead of the US in terms of survival, the percentage of obese men and women actually grew faster in most of those countries between 1975 and 2005. Finally, examining homicide and traffic fatalities, the researchers found that they have accounted for a stable share of U.S. deaths over time, and would not account for the significant change in 15-year life expectancy the study identified.

The researchers say that the failure of the U.S. to make greater gains in survival rates with its greater spending on health care may be attributable to flaws in the overall health care system. They point to the role of unregulated fee-for-service payments and our reliance on specialty care as possible drivers of high spending without commensurate gains in life expectancy.

“It was shocking to see the U.S. falling behind other countries even as costs soared ahead of them,” said lead author Peter Muennig, assistant professor at Columbia University’s Mailman School of Public Health. “But what really surprised us was that all of the usual suspects — smoking, obesity, traffic accidents, and homicides — are not the culprits. The U.S. doesn’t stand out as doing any worse in these areas than any of the other countries we studied, leading us to believe that failings in the U.S. health care system, such as costly specialized and fragmented care, are likely playing a large role in this relatively poor performance on improvements in life expectancy.”

“This study provides stark evidence that the U.S. health care system has been failing Americans for years,” said Commonwealth Fund President Karen Davis. “It is unacceptable that the U.S. obtains so much less than should be expected from its unusually high spending on health care relative to other countries.” The good news is that the Affordable Care Act will take significant steps to improve our health care system and the health of Americans by expanding health insurance, improving primary care, and holding health care organizations accountable for their patients’ overall health and ensuring the coordination of primary care and specialty care to eliminate errors, waste of patients’ time, and wasteful duplication of tests and services.”

Editor’s Note: This article is not intended to provide medical advice, diagnosis or treatment.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Commonwealth Fund, via EurekAlert!, a service of AAAS.

Journal Reference:

1. Peter A. Muennig, Sherry A. Glied. What Changes In Survival Rates Tell Us About US Health Care. Health Affairs, 2010; DOI: 10.1377/hlthaff.2010.0073

The accumulation of misfolded protein marks the accrual of years as the body ages. Could heat shock proteins be used to reduce the effects of aging and diminish the risk of disease by untangling improperly folded proteins?

What does a molecular thermometer look like? This seemed to be a simple question, not much different from the many science fair projects I had done in grade school and high school in Chicago. But rather than the simple solutions I’d present on triptych posterboards, the answer to this question has kept me fascinated for my entire career. The cell’s thermometer appears to be a network of stress-sensing transcription factors and specialized proteins—molecular chaperones—that function as the guardian of the proteome, sensing damage and keeping the cell’s proteins properly folded as they roll off the production line of ribosomes. Exciting as that was, none of us working on this question at the time could have predicted that this thermometer might also control the body’s fountain of youth and provide new ways of thinking about disease.

Proteins are fundamental building blocks for the cell; they are the predominant products of the genome that provide much of the shape and functionality of cells, tissues, and organisms. The proper synthesis, folding, assembly, translocation, and clearance of proteins is essential for the health of the cell and the organism. Proteins also provide the essential parts to replenish molecular machines for biosynthetic processes and ensure their efficient functioning in the adult cell, a process critical for longevity. At the root of the problem is a fundamental process: protein folding. When quality control—as overseen by heat shock proteins and molecular chaperones—slips, errors occur and persist. This interferes with molecular processes, which can lead to disease. When these events occur in neurons, the consequences can be devastating, leading to major classes of neurological disorders, like multiple sclerosis, Huntington’s disease, Parkinson’s disease, and Alzheimer’s disease.

I first became intrigued by heat shock proteins while listening to a seminar by Matt Meselson, who was visiting the University of Chicago to receive an honorary doctorate in the late 1970s. At the time, I had just begun my second year as a graduate student in Murray Rabinowitz’s laboratory in the Department of Biochemistry. While the seminar piqued my interest in this newly discovered heat shock response, it was through my subsequent conversations with Susan Lindquist—who had completed her research with Meselson and had just recently arrived on campus as a postdoctoral fellow—that I really began to appreciate the complexities of this biological response to stress.

In between my efforts to complete my thesis research on the yeast mitochondrial genome and compete in intramural sports with our team, the Kimwipes, I made time to learn more from Lindquist about the heat shock response. Discovered in 1962 by Ferruccio Ritossa, the heat shock response was described as the temperature-induced change in the organization of the tightly packed Drosophila salivary gland chromosome, leading to the appearance of puffs.

Ritossa’s “heat shock” puffs, which by light microscopy looked like cotton balls compressed between sections of tightly packed chromosomes, were also induced by exposure to dinitrophenol, ethanol, and salicylate. However, it was the demonstration that these puffs were new sites of transcription that was most impressive—Ritossa could detect newly synthesized RNA within minutes of puffing. The significance of this was soon revealed by Lindquist and Steven Henikoff in the Meselson lab and Allan Spradling with Mary-Lou Pardue at MIT. These heat shock–induced messenger RNAs encoded a set of proteins, now widely known as the heat shock proteins. These are widely studied as Hsp90, Hsp70, and a family of proteins that guide conformation and folding, and prevent misfolding in cells of all species.

Using a clever trick of cellular biochemistry to enrich for heat shock messenger RNA, the laboratories of David Hogness at Stanford, Walter Gehring at University of Basel, Brian McCarthy at UCSF, Alfred Tissieres at the University of Geneva, and Meselson all cloned the first heat shock genes from Drosophila in the late 1970s and early 1980s.

Heat shock: Exposure of cells to heat shock or other forms of physiological stress elevates the level of misfolded proteins. Accumulation of damaged proteins is prevented by induction of the heat shock response and the expression of heat shock proteins (Hsp90, Hsp70, and Hsp27). Cells at normal temperature have mostly native proteins and heat shock transcription factors in an inactive state. Upon heat shock, proteins misfold and heat shock factors are activated and result in the elevated expression of heat shock genes. In the stress-protected cell, heat shock proteins stabilize misfolded proteins, prevent the formation of aggregates, and enhance the levels of native functional proteins.

Heat shock factors in aging: As the cells in an organism age, proteins lose their integrity and appear as misfolded molecules that can aggregate. In the young cell, proteins are mostly in the native folded state. During aging, misfolded proteins appear and can form protein aggregates that interfere with cellular function. The youth recovered state can be attained by enhanced activity of heat shock transcription factor to elevate the levels of heat shock proteins in the cell, thus reducing the appearance of damaged proteins.

By this time, I had received my PhD from Chicago and was a postdoc with Matt Meselson in the Harvard biolabs. During this period, I became intrigued with the possibility that heat shock genes might be expressed in other eukaryotes. The counter opinion at the time was that heat shock response was a fruit fly thing. While in hindsight this might seem an odd and naïve question, our knowledge in the early 1980s was very limited and there was no reason to assume that a temperature response in fruit flies should have anything to do with humans. Moreover, the concepts of heat shock proteins as molecular chaperones would not appear for nearly another decade. Nevertheless, armed with the newly developed method of Southern blotting, I decided to search for the heat shock genes in other eukaryotes. Being located in the Harvard biolabs where there was an impressive collection of organisms under investigation, it was just one day’s work to wander the long halls with an ice bucket and return with genomic DNA from a wide array of life’s creatures. After running my collection of DNA on an agarose gel and incubating the nitrocellulose transfer paper with my radiolabeled Hsp70 gene fragments, I searched for the DNA fragments that were complementary.

I still remember the water dripping down my arm as I pulled out the developed X-ray film and saw bands of different sizes in each of the lanes of the gel. Hsp70 was everywhere and in all eukaryotic genomes, including humans’. The characterization of the human Hsp70 gene then became the focus of my new laboratory in the Department of Biochemistry, Molecular Biology, and Cell Biology at Northwestern University in Evanston, Ill. Around the same time, Jim Bardwell and Betty Craig at the University of Wisconsin at Madison had identified a gene in E. coli, dnaK, which was the bacterial equivalent of Hsp70, leading to the realization that heat shock genes were essentially identical from bacteria to humans and subsequently shown to be present in all five kingdoms.1

None of us working on this question at the time could have predicted that this thermometer might also control the body’s fountain of youth and provide new ways of thinking about disease.

With the cloning of human Hsp70 and subsequently other members of the human Hsp70 gene family, our efforts at Northwestern initially focused on learning how this gene was regulated in fruit flies. While looking for sequence homologies across species, we spent a lot of time looking at the regulatory regions of the human heat shock genes that would be bound by the heat shock transcription factor. Efforts mostly from Carl Wu at NIH, Bob Kingston at Harvard, John Lis at Cornell, and my lab led to the identification of a family of heat shock transcription factors that controlled the first step of the heat shock response. Was this the molecular thermometer that I had been searching for? These heat shock factors changed their shape when the temperature changed, binding to the heat shock gene promoters and initiating the expression of heat shock genes (see graphic below). Moreover, humans expressed three such heat shock factor genes—as opposed to one in yeast, Drosophila, and C. elegans—suggesting that these genes, with such exquisite regulation, might have other functions that we had yet to discover.

Additional insights on the molecular thermometer came from studies showing that the heat shock proteins were regulating the very transcription factor that initiated their production in the nucleus. The function of heat shock proteins as molecular chaperones to guide folding, to ensure alternate conformational states, and to recognize and suppress misfolding was becoming well established. Therefore, the cellular thermometer wasn’t just measuring temperature, it also monitored for the appearance of damaged proteins. Heat shock and other stressors would lead to a flux of misfolded and damaged proteins, shifting the chaperone equilibrium in the cell toward capturing these damaged proteins and releasing Hsf1 to self-associate and form trimers capable of binding to the heat shock elements in the genome. The chaperones, therefore, had yet another role: to repress the transcriptional activity of Hsf1, providing a feedback loop for the heat shock response when sufficient levels of heat shock proteins were available.

As my lab started exploring the normal functions of heat shock proteins in the cell, I began to feel somewhat constrained by the human tissue culture cell lines we had been using. While the cells allowed us to probe the identity and function of the relevant molecules, it was unclear how these changes related to a whole organism. In around 1999, we introduced C. elegans into our lab as a new model system to address a question on the regulation of the heat shock response. We drew inspiration from a 1994 paper by Max Perutz showing that a mutation in polyglutamine that caused the protein to aggregate was responsible for Huntington’s disease, a profound and devastating neurodegenerative disease. In short time, C. elegans became our system of choice for exploring new stress signals such as the expression of expanded polyglutamine proteins.2 Could misfolded proteins, as prompted by the expression of polyglutamine, provide insights into the molecular thermometer?

Buoyed by these possibilities, I submitted the renewal for my long-standing NIH grant and was nominated for a Merit Award. This gift of 10-year support from the National Institute of General Medical Sciences (NIGMS) came at exactly the right time. In addition to developing new animal models for expression of polyglutamine expansion in neurons and muscle cells, we observed that the aggregation and associated toxicity of these proteins was proportional to their length and also to the age of the animal. This led us to ask whether suppressing the insulin signalling pathways that regulate lifespan might affect the aggregation of polyglutamine. The results showed a clear relationship,3 moreover subsequent studies revealed that Hsf1 was essential for lifespan via the insulin signalling pathway. These observations revealed that the heat shock response was not only important for survival of acute stress but equally for day-to-day events of protein toxicity that could affect the health of the cell’s proteins and lifespan.

By this point, an increasing amount of work in our lab had shifted toward the use of C. elegans, and this whole organismal thinking gave me leeway to probe beyond the concept of stress at a cellular level to begin to address how the animal senses and integrates external information at the molecular level. If stress affected aging, then perhaps these heat shock proteins that sensed and protected the cell from accumulated damage might help slow the effects of aging.
Ritossa’s “heat shock” puffs, which by light microscopy looked like cotton balls compressed between sections of tightly packed chromosomes, proved to be new sites of transcription.

Because we had earlier observed that many diseases associated with aggregation-prone proteins exhibit age-related phenotypes and that all protein misfolding diseases are associated with aging, it seemed logical to ask whether temperature-sensitive metastable proteins lost function during aging. We had observed earlier that polyglutamine expressed in different tissues of C. elegans caused temperature-sensitive proteins in the same tissue to completely misfold and aggregate. This result really turned our heads, for none of us had expected that a single aggregation-prone protein would have such global effects! Indeed, when the same temperature-sensitive proteins were followed during aging alone, we observed that they all misfolded and lost function early on in natural aging.4 When I saw these results, I was shocked. It suggested that the machines that keep proteins folded properly would have already started to fall apart as an organism reaches maturity. Returning to Hsf1, we learned that the heat shock response and other cytoprotective responses were compromised during aging. However, despite the rather profound consequences of these observations, we found that activation of Hsf1 in early development could suppress this collapse of protein-folding homeostasis (proteostasis). The implications are intriguing. While it is always possible that such observations do not extend to more complex metazoans, we are all made of proteins and it seems likely that the tales of worms may help us understand human aging.

But there was more to the story. Our recent work suggests there may be ways of modulating proteostasis that don’t involve interfering with Hsf1 directly. We decided to plunge into a classical genetic screen of C. elegans mutants that demonstrated protein misfolding in the muscle cells. While one might have expected to get many of the same genes already identified, we found something completely new. The mutation that affected misfolding in the muscle cell corresponded to a transcription factor that controls the production of the neurotransmitter GABA, responsible for mediating excitatory neurotransmitters and controlling muscle tone! Remarkably, any imbalance in the GABA pathway leading to overstimulation caused the postsynaptic muscle cell to think it was stressed and to start misfolding proteins.5 Suddenly, the molecular thermometer got more complicated with the realization that the activity of neurons could affect the thermometer of another cell.
Many human diseases thought to be unrelated may share commonalities of defects in protein folding homeostasis.

If this mechanism also occurs in humans, we may be able to find the neuronal signature that controls protein misfolding in cells and activate the heat shock proteins in the skeletal muscle system to help restore function in muscular dystrophy and other motor neuron diseases. The findings also tease the possibility that there might be a way to control, stall, or regulate the misfolding associated with aging via a neurological mechanism. However, the story with neurons seems to be more nuanced. We observed that two neurons in C. elegans control the regulation of the heat shock response in all adult somatic cells. The role of active neuronal signalling and feedback control would seem to provide a basis by which cells and tissues activate a heat shock response according to need. This makes sense, as different tissues will have varied protein biosynthetic needs and environmental exposures. A “one-size-fits-all” approach to the heat shock response would not work.

With these exciting ideas that our research has led us to ponder, I and several of my colleagues (Jeff Kelly at The Scripps Research Institute and Andy Dillin at the Salk Institute) cofounded Proteostasis Therapeutics in Cambridge, Mass., to discover small molecule therapeutics that could correct the effects of misfolded proteins in disease. The approach is not without risk—the level of heat shock proteins are increased in many cancers—but the promise of the technology is certainly too exciting not to explore.

The heat shock response is a good story. It has humble beginnings of pure curiosity. Starting with a small band of “heat shockers,” the field has grown immensely and encompasses a multitude of disciplines and approaches fundamental to biology. In it are all of the elements of intrigue and surprise, with a remarkable cast of characters. Who would have predicted the chance observation of Ritossa’s that chromosomal puffs in Drosophila, induced by elevated temperature, would lead to discoveries across all of biology? Well beyond the satisfaction of these observations alone has been the recognition that many human diseases thought to be unrelated may share commonalities of defects in protein folding homeostasis and that the correction of these defects could have broad-reaching global effects on proteome stability and the health of the cell. All throughout this, I have been fortunate to have a wonderful family—my wife Joyce and children Emiko and Kenji and a fantastic set of colleagues and lab members. Perhaps the efforts to apply the discoveries of heat shock proteins successfully to maintaining health and curing disease is one way to thank them for their enthusiastic support.

BY RICHARD MORIMOTO
Richard Morimoto is the Bill and Gayle Cook Professor of Biology and director of the Rice Institute for Biomedical Research at Northwestern University, and a cofounder of the Proteostasis Therapeutics, Inc. in Cambridge, Mass.

References:
1. C. Hunt, R.I. Morimoto, “Conserved features of eukaryotic hsp70 genes revealed by comparison with the nucleotide sequence of human hsp70,” Proc Natl Acad Sci USA, 82:6455–59, 1985.
2. S.H. Satyal et al., “Polyglutamine aggregates alter protein folding homeostasis in Caenorhabditis elegans,” Proc Natl Acad Sci USA, 97:5750–55, 2000.
3. J.F. Morley et al., “The threshold for polyglutamine-expansion protein aggregation and cellular toxicity is dynamic and influenced by aging in Caenorhabditis elegans,” Proc Natl Acad Sci USA, 99:10417–22, 2002.
4. A. Ben-Zvi et al., “Collapse of proteostasis represents an early molecular event in Caenorhabditis elegans aging,” Proc Natl Acad Sci USA, 106:14914–19, 2009.
5. S. Garcia et al., “Neuronal signaling modulates protein homeostasis in Caenorhabditis elegans postsynaptic muscle cells,” Genes Dev, 21:3006–16, 2007. PMCID: PMC2049200

Read more: Shock and Age – The Scientist – Magazine of the Life Sciences http://www.the-scientist.com/article/display/57461/#ixzz0qs5xHTP4

Mahatma Gandhi was once asked by a reporter what he thought about western civilization, and in light of the uncivilized treatment by the British government of his nonviolent actions, he immediately replied, “Western civilization? Yes, it is a good idea.” Likewise, if he were asked what he thought about “scientific medicine,” he would probably have replied in a similar manner.

The idea of scientific medicine is a great one, but is modern medicine truly, or even adequately, “scientific”?

Modern medicine uses the double-blind and placebo-controlled trial as the gold standard by which the effectiveness of a treatment is determined. On the surface, this scientific method is very reasonable. However, serious problems in these studies are widely acknowledged by academics but remain unknown to the general public. Fundamental questions about the meaning of the word “efficacy” are rarely raised.

For instance, just because a drug treatment seems to eliminate a specific symptom does not necessarily mean that it is “effective.” In fact, getting rid of a specific symptom can be the bad news. Aspirin may lower your fever, but physiologists recognize that fever is an important defense of the body in its efforts to fight infection. Sleep-inducing drugs may lead you to fall asleep, but they do not lead to refreshed sleep, and these drugs ultimately tend to aggravate the cycle of insomnia and fatigue, while conveniently (for the drug companies) tend to create addiction. Long-term safety and efficacy of many modern drugs for common ailments remains unknown, despite the high hopes and sincere expectations from the medical community and the rest of us for greater certainty.

The bottom line to scientific research is that a scientist can set up a study that shows the guise of efficacy. In other words, a drug may be effective for a very limited period of time and then cause various serious symptoms. For example, a very popular anti-anxiety drug called Xanax was shown to reduce panic attacks during a two-month experiment, but when individuals reduce or stop the medication, panic attacks can increase 300-400 percent (Consumer Reports, 1993). Would many patients take this drug if they knew this fact, and based on what standard can anyone honestly say that this drug is “effective”?

To get FDA approval to market a drug, most of the studies for psychiatric conditions last only six weeks (Angell, 2004, 112). In view of the fact that most people take anti-depressant or anti-anxiety medicines for years, can these short studies be scientifically valid? What is so little known and so sobering is that research to date has found that placebos are 80 percent as effective and have fewer side effects and a lot cheaper (Angell, 2004, 113).

Marcia Angell, MD, the former editor of the New England Journal of Medicine and author of the powerful book The Truth about Drug Companies, said it plainly and directly: “Trials can be rigged in a dozen ways, and it happens all the time” (Angell, 2004, 95).

She further expresses real concern about research reliability:

It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgment of trusted physicians or authoritative medical guidelines. I take no pleasure in this conclusion, which I reached slowly and reluctantly over my two decades as an editor of The New England Journal of Medicine. As reprehensible as many industry practices are, I believe the behavior of much of the medical profession is even more culpable.

Angell gives many examples of why reading research studies is not reliable:

A review of 74 clinical trials of antidepressants, for example, found that 37 of 38 positive studies were published. But of the thirty-six negative studies, thirty-three were either not published or published in a form that conveyed a positive outcome (Turner, 2008).

Conventional drugs used today are so new that there is very little long-term research on them. There are good reasons why a vast majority of modern drugs used just a couple of decades ago are no longer prescribed: they don’t work as well as previously assumed, and/or they cause more harm than good.

Sadly and strangely, many physicians do not see that there is something fundamentally wrong with the present medical model. Once a drug is found to be ineffective or dangerous, doctors and drug companies simply find another drug that, at least initially, seems to have good short-term results, that is, until longer term studies establish that it doesn’t work as well as assumed and/or is more dangerous. Although some people consider these failures as evidence of the wisdom of the scientific process, these problems are evidence of the limitations of a model of medicine that over-emphasizes a biochemical, biomechanical pharmacological approach to healing that ultimately seeks to “attack” disease, “combat” illness, and wage “war on cancer” or on the human body itself (Ullman, 2009) This paradigm can be invaluable in emergency medicine and help us survive certain infectious diseases, but for the large majority of people facing day-to-day chronic illnesses, it provides short-term results, serious side-effects, and stratospherically high costs.

The vast majority of drugs have a quick turnover in the medical marketplace, making them more akin to fashion more than science. Despite this recurrent pattern, doctors are prescribing drugs at record-breaking rates. Polypharmacy (the use of more than one drug concurrently for a patient) is becoming routine, even though there is very little evidence for the safety or efficacy of such practice. Some scary details about the serious problems that result from polypharmacy was discussed in an earlier article.

The primary reason that modern medicine fails so many times is that it tends to assume that symptoms are just something “wrong” with the person that then needs to be managed, controlled, or suppressed. Distinct from this medical viewpoint is an ancient and futuristic model that recognizes that symptoms represent DEFENSES of the body that should be nurtured and augmented as a way to treat disease processes. This latter approach to treating the sick is the naturopathic and homeopathic models of the West, the Ayurvedic approach of India, and the various styles of acupuncture from the East.

One hopes that the American public would greatly benefit from receiving the “best” and certainly most expensive care that modern medicine has to offer. However, this simply isn’t true. In fact, the following statistics powerfully state the results from what some people mistakenly refer to as the “best” medical care in the world:

• According to 2006 data, the infant mortality rate in the United States was ranked twenty-first in the world, worse than South Korea and Greece and only slightly better than Poland.
• Data from 2006 also showed that the life expectancy rate in the United States was ranked seventeenth in the world, tied with Cyprus and only slightly ahead of Albania (InfoPlease, 2007).

Even “Good” Research is Often Bad
Medications that can allay pain or any type of serious discomfort are a great blessing, but let’s not fool ourselves into believing that modern pain drugs are curative agents. In fact, although they provide blessed short-term relief, they create their own pathology, addiction, and demand for increasing doses over time.

Such pain relief is akin to unscrewing a warning light in your car. It does turn off that irritating light, though it does nothing to change the underlying problem.

However, when a drug company’s scientific trial “proves” that their drug reduces pain, it then markets this treatment as “scientifically proven” and is able to sell the drug to doctors and to consumers with a marketable spin that makes them the big bucks. What is so brilliant about the cozy relationship that drug companies have with “science” is that most people have insurance these days and don’t have to pay out-of-pocket for these “proven” drugs. Even though their (and our) insurance premiums sky-rocket, many employers distance the patient from the real costs of paying the bill.

It is so impressive how proving that one can use conventional drugs to “unscrew a warning light” can make big big bucks. My previous article noted that the combined profits ($35.9 billion) of the ten largest drug companies in the Fortune 500 in 2002 were more than the combined profits ($33.7 billion) of the remaining 490 companies together (Angell, 2004, 11). In a civilized world, no industry should have this amount of profit without being considered a criminal enterprise.

And let’s also not fool ourselves into believing that conventional medical treatment is the sole method of providing pain relief. Back in 1983, I coined the term “medical chauvinism” as a common assumption that there is only one type of education with which to learn the science and art of healing or that there is only one type of health professional suitable to provide health care (Ullman, 1983a; 1983b). Despite its recent prevalence, medical chauvinism is an anomaly historically and internationally.

Equally problematic to medical chauvinism is “scientism,” which is the common assumption that science is the only way to acquire knowledge about reality. There is a great amount of human experience that cannot be tested in a “double-blind and placebo controlled trial,” and the lack of “scientific evidence” for these experiences does not make them invalid, unproven, or non-existent.

It is more than a tad ironic that there are extremely few double-blind and placebo-controlled trials testing surgical procedures, and yet, physicians and skeptics do not refer to surgery as “quackery.” Surgeons appropriately note that it is impossible to conduct such studies because it is unethical to open up a patient for surgery to provide a “placebo surgery.” And yet, these same physicians and skeptics use this offensive term, “quackery,” with regularity and without parity, to a host of alternative therapies that have similar challenges to providing placebo treatment. How does one give a placebo meditation, and how can many naturopathic protocols be tested when the combined treatment regiment includes an herb, a vitamin, a homeopathic medicine, AND some type of physical therapy.

Scientism is a type of fundamentalism where science is the religion (Milgrom, 2010). A significant problem with scientism is that its believers are often even more arrogant than religious fundamentalists. Perhaps worse, they don’t even acknowledge that their belief system is a belief system. This problem may explain the lack of humility of many doctors and scientists.

Understanding and Rewriting History

Who controls the past controls the future: who controls the present controls the past.
George Orwell, author of 1984

History provides us with diverse evidence about our past, but ultimately, only a small portion is told in history books. The interpretation of our past and the select use of facts and figures influence our understanding of what happened.

Historians commonly remark that whichever country wins a war or whichever worldview dominates another, the history is told through that country’s perspective or that dominant point of view. This is certainly true in the history of medicine. For instance, medical historians commonly portray conventional medical practice of the past as barbaric and dangerous, and yet they have asserted that today’s medical care is at the apex of “scientific medicine.” The assertion that today’s medical care is “proven” is a consistently repeated mantra.

History also tends to portray those who lose a war and who represent a minority point of view as having less than positive attributes. For instance, those physicians practicing medicine differently than the orthodox medical practice might be called cranks, crackpots and quacks. Such name-calling is a wonderfully clever way to trivialize potentially valuable contributions, whether or not one understands what these contributions really are.

Besides name-calling, practitioners of the conventional and dominating paradigm often spin facts to make the strong and solid features of a minority practice into something strange and weird. Homeopaths are accused of using smaller doses than used in orthodox medicine, and this is portrayed as homeopaths using doses that “theoretically” could not have any physiological effect. The medical fundamentalists purposefully ignore the significant literature that posits different theories about how homeopathic medicines work (Chaplin, 2010; Bellavite and Signorini, 2004; Homeopathy, 2010), and they (again) show their lack of humility because there are innumerable conventional medical treatments today for which the mechanism of action remains unknown. Even good skeptics know that we still do not understand how tobacco smoking causes cancer, and yet, no one advocates that we ignore this good health information just because the precise mechanism remains a mystery (Spector, 2010).

Accusations that homeopathic medicines could not possibly have any effect are made without knowledge, experience or humility. Such accusations simply become evidence of the accuser’s unscientific attitude and his or her ignorance of the diverse body of basic scientific work on the effects of nanodoses of certain substances in specific situations.

The fact that homeopaths have used their medicines for more than 200 years is spun as evidence that this system of medicine has not “progressed.” Another interpretation here is that the same homeopathic medicines used 200 years ago are still used today, along with hundreds of new ones, primarily because the old ones still work. The art of using homeopathic medicines is that they are not prescribed for a localized disease but for a syndrome or pattern of symptoms of which the localized disease is a part. It is clever how some people try to spin positive attributes in hyper-negative ways.

The fact that homeopaths interview a patient to discover his or her unique symptoms has been spun to make homeopathy seem like a quirky system that revels in inane facts about a patient. However, the detailed symptoms and characteristics of the patient that homeopaths collect may not be comprehended by those unfamiliar with the unique and critical nature of individualizing features in each person. Homeopathy provides a sophisticated method by which a patient’s characteristics are applied to selecting and prescribing the most effective homeopathic medicine. Today, a large majority of practicing homeopaths use expert system software to help them prescribe their medicines in a highly individualized way to patients.

Homeopaths use the term “vital force” in a fashion similar to how acupuncturists use the term “chi” to refer to the underlying forces in a living system that connects mind and body. Although antagonists to these systems of natural medicine try to make them sound “woo-woo,” homeopaths and acupuncturists confidently respond by asserting that living systems are not machines or simply bodies of chemical interactions.

I personally have no problem with “skeptics” of homeopathy, though most people who think of themselves as skeptics are really simply “deniers” or “medical fundamentalists.” A skeptic is one who may not believe that homeopathy works, but che (my preferred alternative to s/he) strives to be familiar with the body of literature, not just the “negative” trials. Further, a good skeptic evaluates clinical trials, basic science trials, animal studies, cost-effectiveness comparisons, outcome studies, consecutive case reports, and epidemiological data. A good skeptic is simply a good scientist who evaluates a whole body of evidence.

Sadly, most deniers of homeopathy simply and directly lie about the subject. They commonly assert that “there is no research on homeopathy” or “there is no possible mechanism of action for how homeopathic medicines work”. These fundamentalists KNOW that this is not true. Several of my previous articles have referenced this body of evidence (Ullman, 2009b; Ullman 2010a, Ullman, 2010b).

Some of the most recent reviews of research include one meta-analysis of clinical research published in the prestigious Journal of Clinical Epidemiology (Ludtke, Rutten, 2008) and two full issues of the peer-review journal, Homeopathy (2009, 2010) which reviewed basic sciences research.

What is so interesting to watch is the questionably honest or ethical behavior of these medical fundamentalists. They have been informed of the many studies and meta-analyses that have verified the clinical efficacy of homeopathic medicines, as well as hundreds of basic sciences trials, many of which have been replicated by other researchers. One review of replications of basic science work is of special interest (Endler, et al, 2010).

The deniers of homeopathy love to say that homeopaths “cherry-pick” the positive studies and ignore the negative ones. They then incredulously assert that we should ignore ALL of the positive trials. Such statements and viewpoints are profoundly misguided and simply daft. Will these same people say that Thomas Edison “cherry-picked” his positive study and ignored all of his “negative” studies in his efforts to invent electric lights? The (il)logic of the deniers is that they would recommend ignoring Edison’s discovery because the vast majority of his studies were not positive.

Finally, medical history sheds light on what is and isn’t real.

In 1832, the esteemed founder of homeopathy, Samuel Hahnemann, MD, was granted honorary membership in the Medical Society of the City and County of New York. And yet, 11 years later, the minutes of this medical society confirm that once this conventional medical association recognized the “major ideological and financial threat” that the growth of homeopathy represented, the medical society rescinded his membership (Gevitz, 1988, p. 102). It is the ideological and financial threat that homeopathy poses that motivates the antagonism to it, not whether it works or not.

In light of the fact that history tends to be written by the victors, this writer predicts that history will soon be rewritten.
References

Angell M. The Truth about Drug Companies. New York: Random House, 2004. This fact is extremely startling, but the source is reputable: Marcia Angell, MD, is former editor of the New England Journal of Medicine.

Angell M. Drug Companies & Doctors: A Story of Corruption. The New York Review of Books. 56, 1: January 15, 2009. http://www.nybooks.com/articles/archives/2009/jan/15/drug-companies-doctorsa-story-of-corruption/

Bellavite P and Signorni A. The Emerging Science of Homeopathy: Complexity, Biodynamics, and Nanopharmacology. Berkeley: North Atlantic, 2002.

Chaplin M. Water Structure and Science. London South Bank University. http://www1.lsbu.ac.uk/water/homeop.html and http://www1.lsbu.ac.uk/water/memory.html

Consumer Reports, High Anxiety. January 1993, 19-24.

Endler PC, Thieves K, Reich C, Matthiessen P, Bonamin L, Scherr C, Baumgartner S. Repetitions of fundamental research models for homeopathically prepared dilutions beyond 10-23: a bibliometric study. Homeopathy, 2010; 99: 25-36

Gevitz N. The Other Healers: Unorthodox Medicine in America. Baltimore: Johns Hopkins University: 1988.

Homeopathy (a peer-review journal published by Elsevier) (October, 2009)

Homeopathy (January, 2010)

Levi R. Science Is for Sale, Skeptical Inquirer, July/August 2006, 30:4, 44-46.

Ludtke R, Rutten ALB. The conclusions on the effectiveness of homeopathy highly depend on the set of analyzed trials. Journal of Clinical Epidemiology. October 2008. doi: 10.1016/j.jclinepi.2008.06/015.

Milgrom L. Beware scientism’s onward march.

Roberts WH. Orthodoxy vs. homeopathy: Ironic developments following the Flexner Report at the Ohio State University, Bulletin on the History of Medicine, Spring 1986, 60:1, 73-87.

Spector R. The War on Cancer: A Progress Report for Skeptics. Skeptical Inquirer. January/February, 2010.

Turner EH, et al., “Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy,” The New England Journal of Medicine, January 17, 2008

Ullman D. Beyond Medical Chauvinism, California Living (the Sunday supplement magazine of the San Francisco Chronicle and San Francisco Examiner, August 21, 1983a, 4-7.

Ullman D. Medical Monopoly vs. Alternative Health Care, Social Policy, Summer, 1983b, 27-28.

Ullman D. 2009a. When Militarism ‘Invades’ Medicine…Doctatorship Happens

Ullman D. 2009b. The Epidemic Of ‘Medical Child Abuse’ And What Can Be Done.

Ullman D. 2010a. The Case FOR Homeopathic Medicine: The Historical and Scientific Evidence

Ullman D. 2010b. Homeopathic Medicine: Europe’s #1 Alternative for Doctors

Walsh JJ. History of the Medical Society of the State of New York. New York: Medical Society of the State of New York, 1907.

By Jim English

Clinical Trial of Age-Related Health Problems in 150 Adults

Research on an advanced anti-aging formula shows how the herbal combination works to counter a host of problems commonly associated with human aging. By supporting healthy microcirculation this anti-aging herbal formula has been shown to enhance energy levels, reduce plasma viscosity, enhance microcirculation and reverse capillary damage. Additionally, by promoting improved internal organ function and speeding removal of cellular waste products such as lipofuscin, the formula aids in supporting the immune system to increase resistance to illness and improve overall health. The following is a summary condensed from a large clinical trial involving 150 patients, aged 55 to 89 years old. In their paper the study researchers documented significant improvements in a wide range of symptoms commonly associated with age-related degenerative health issues.
Arterial Support

With advancing age, arteries tend to thicken as fatty deposits accumulate on the inner lining of arterial walls, especially in the coronary and cerebral arteries. These deposits reduce arterial circumference and impair blood vessel elasticity, resulting in reduced blood flow to heart tissues. Common symptoms usually include chest distress, palpitations, insomnia, and pain due to insufficient blood supply to the coronary arteries.

Angina: Prior to treatment, 25 of the enrolled patients had been diagnosed with angina pectoris (chest pain or discomfort due to coronary heart disease and reduced blood flow to the heart). After one month of taking the anti-aging herbal formula, 23 of the 25 patients (92 percent) were completely free of symptoms, and the remaining two patients reported that their symptoms were significantly reduced.

Chest Tightness: Before receiving the anti-aging herbal formula, 106 patients reported experiencing chest pains. After receiving the formula for one month, only two of the 106 patients (1.3 percent) continued to feel chest pains.

Palpitations: Of 86 patients experiencing unpleasant sensations, including irregular and/or forceful beating of the heart, 82 reported complete relief from symptoms one month after treatment, and only four patients reported continued symptoms.
Coughing, Shortness of Breath

Human aging is associated with the partial or complete wasting (atrophy) of the adrenal cortex and sex glands, resulting in deterioration of the mononuclear phagocyte system (part of the immune system) and a decline in antibody production for protection from infection. Other factors, such as a narrowing or obstruction of the pulmonary arteries, contribute to inflammation of the bronchial walls, resulting in lung congestion, edema, fibroplastic proliferation and narrowing of the bronchial tubes. Symptoms often include chronic coughing and shortness of breath.

Coughing: Before receiving the anti-aging herbal formula, patients were questioned about their coughing patterns. Coughing fits lasting five minutes or longer, and occurring in both the morning and evening, were considered diagnostically relevant. Thirty-six patients reported that they experienced bouts of coughing lasting longer than five minutes in both morning and evening. After taking the anti-aging herbal formula for one month, 34 patients reported improvement (94 percent), and only two cases reported coughing fits still lasting for more than five minutes.

Shortness of Breath: To determine shortness of breath, all 150 patients were required to climb one flight of stairs, after which their breathing was monitored and recorded. These records were compared to records gathered at intake. At the start of the study, 42 patients experienced shortness of breath during the stair test. At the conclusion of the study only seven patients still experienced shortness of breath, while 35 patients (83 percent) were able to complete the stair test without difficulty.
Dizziness

Dizziness is one of the most common complaints of the elderly. Originating in the central vestibule of the brain stem, age-related dizziness is often related to impaired blood flow caused by hardening of the arteries. Prior to the trial, 69 patients reported experiencing bouts of dizziness. After one month of treatment, 59 patients (85 percent) reported that their symptoms had abated, while only 10 patients (15 percent) still experienced episodes of dizziness.
Edema, Puffiness of Lower Limbs

In the elderly, as plasma albumin levels decrease, colloid osmotic pressure of the plasma is reduced as well. Additionally, as aging blood vessels become increasingly permeable, plasma levels of sex hormones decline, leading to increased retention of water and sodium. Together these changes contribute to increased accumulation of fluid (edema) and swelling in the lower limbs. The anti-aging herbal formula has previously been shown to increase plasma albumin and sex hormone levels, leading researchers to theorize that the formula would aid in reducing lower limb edema. Prior to administration of the formula, 32 subjects were diagnosed with edema of the lower limbs, including edema resulting from chronic heart failure and chronic renal dysfunction. After one month of treatment with the anti-aging herbal formula, 30 patients (94 percent) were free of edema, and only two patients still showed signs of swelling of the lower limbs.
Loss of Appetite

The gradual decline of the hypothalamus-pituitary-adrenal cortex is a hallmark of human aging. As the thyroid glands deteriorate, secretion of digestive enzymes and gastric juices are reduced, resulting in a loss of appetite. Before receiving the formula, 56 patients suffered from diminished appetite. At the conclusion of the study, 49 patients (87 percent) reported that their appetite had returned, and only seven patients continued to show signs of poor appetite after treatment.
Blood Pressure

In the elderly, elevated systolic and diastolic blood pressure levels result from the loss of elasticity in the arterial walls. Other contributing factors include narrowing of the diameter of blood vessels, increased resistance to peripheral blood flow, and elevated blood serum viscosity. The anti-aging herbal formula has been shown to exert positive anti-aging effects to aid in normalizing blood pressure levels. Researchers measured blood pressure levels of patients before and after treatment with the formula. Of the 150 volunteers, only those with a systolic pressure greater than 160 and a diastolic pressure greater than 90 were selected for further evaluation, for a total of 62 subjects. Before administration, 26 patients had blood pressure measurements greater than 160/90. The highest systolic pressure was 207, and the highest diastolic pressure was 120. The average systolic pressure was 149, and the average diastolic pressure was 89. After taking the anti-aging herbal formula for 30 days, blood pressure readings greater than 160/90 were seen in only three subjects. The highest systolic pressure of those who were treated was 150, while the average dropped to 127. The highest diastolic pressure fell to 100, while the average fell to 79.
Improved ECG

Of the 150 study patients admitted to the study, 48 had been previously diagnosed with coronary heart disease. Prior to receiving the anti-aging herbal formula, ECG abnormalities were detected in 35 patients, including STT changes, frequent premature atrial beat, atrial fibrillation and frequent premature ventricular beat. Following treatment 30 patients (85 percent) were shown to be free of the previously detected ECG abnormalities, while five patients (15 percent) were found to still have abnormal ECGs.
Blood Flow

Researchers randomly gathered blood samples from 41 patients (20 males and 21 females) prior to treatment and at the end of the study. The examiners conducted the following tests on blood samples:

• Whole-blood specific viscosity

• Erythrocyte sedimentation rate

• Hematocrit (red blood cell count)

• Plasma specific viscosity

• Erythrocyte electrophoresis

While there were no detectible changes in erythrocyte sedimentation rate or hematocrit after treatment, test results revealed significant improvements in whole-blood specific viscosity, plasma specific viscosity and erythrocyte electrophoresis.
Microcirculation

Researchers randomly selected 51 patients to measure circulation in nail-fold microcapillaries prior to receiving the anti-aging herbal formula, and again at the end of the study. Microscopic observations revealed significant improvements in the speed of blood flowing through the microcapillaries of the nail folds after treatment.
Immune Function

To evaluate the anti-aging herbal formula’s impact on immune function, the researchers selected 44 patients for blood tests. Efficiency of cellular immunity was determined by measuring lymphocyte transformation rate, and the immune function of red blood cells was determined by erythrocyte rosette (Erosette) formation.

Lymphocyte Transformation Rate: The average value before administration of the anti-aging herbal formula was 53.944. This value rose to 59.444 after one month of treatment. This was a considerable increase showing statistical significance (P<0.05).

Test of Rosette Formation: Average value prior to administration of the formula was 52.176. This value increased greatly to 54.647 after treatment. The difference was statistically significant. (P<0.05).
Metabolism of Plasma Proteins

Albumin is an abundant blood plasma protein produced by the liver and secreted into the blood. In addition to preventing the leakage of fluids from the capillaries into surrounding tissues, albumin aids in transporting small molecules, such as calcium, unconjugated bilirubin, free fatty acids, cortisol and thyroxine. Serum albumin levels can serve as a useful marker of chronic liver disease and nutritional status. Researchers measured albumin levels in 44 patients prior to administration with the formula and again at the end of treatment.

Plasma Albumin: The average value of plasma albumin was 4.573 before administration, and rose to 4.768 by the end of the study. These numbers were statistically significant (P<0.01).

Plasma Globulin: Prior to administration, average plasma globulin was 2.734. This number decreased to 2.564, indicating a statistically significant improvement.

Plasma Albumin/Globulin Ratio: The ratio before treatment was 1.702, and increased to 1.897 following the treatment period. The difference indicated a great statistical significance (P<0.01).
Summary

This new, advanced anti-aging herbal formula has been shown to have excellent therapeutic actions on such elderly disorders as chest tightness, insomnia, chest pains, coughing, shortness of breath, heart palpitations, dizziness and lack of appetite. The formula has been shown to promote healthy blood circulation while supporting expansion of coronary arteries and arterioles of the brain and lungs, increasing blood flow in coronary vessels, improving vessel elasticity, enhancing T-cell immunity and promoting the synthesis and metabolism of proteins.

These findings indicate that the formula can serve as a valuable antiaging formula to aid in reversing various disorders affecting the elderly, such as insufficient blood supply to the brain, coronary heart disease, chronic bronchitis, and hypoproteinemia, without the risk of adverse or toxic side effects.

Tanja Stocks and colleagues carry out an analysis of six European cohorts and confirm that abnormal glucose metabolism is linked with increased risk of cancer overall and at specific sites. Tanja Stocks1*, Kilian Rapp2, Tone Bjørge3,4, Jonas Manjer5, Hanno Ulmer6, Randi Selmer7, Annekatrin Lukanova8, Dorthe Johansen5, Hans Concin9, Steinar Tretli10, Göran Hallmans11, Håkan Jonsson12, Pär Stattin1

Prospective studies have indicated that elevated blood glucose levels may be linked with increased cancer risk, but the strength of the association is unclear. We examined the association between blood glucose and cancer risk in a prospective study of six European cohorts.
Methods and Findings

The Metabolic syndrome and Cancer project (Me-Can) includes cohorts from Norway, Austria, and Sweden; the current study included 274,126 men and 275,818 women. Mean age at baseline was 44.8 years and mean follow-up time was 10.4 years. Excluding the first year of follow-up, 18,621 men and 11,664 women were diagnosed with cancer, and 6,973 men and 3,088 women died of cancer. We used Cox regression models to calculate relative risk (RR) for glucose levels, and included adjustment for body mass index (BMI) and smoking status in the analyses. RRs were corrected for regression dilution ratio of glucose. RR (95% confidence interval) per 1 mmol/l increment of glucose for overall incident cancer was 1.05 (1.01–1.10) in men and 1.11 (1.05–1.16) in women, and corresponding RRs for fatal cancer were 1.15 (1.07–1.22) and 1.21 (1.11–1.33), respectively. Significant increases in risk among men were found for incident and fatal cancer of the liver, gallbladder, and respiratory tract, for incident thyroid cancer and multiple myeloma, and for fatal rectal cancer. In women, significant associations were found for incident and fatal cancer of the pancreas, for incident urinary bladder cancer, and for fatal cancer of the uterine corpus, cervix uteri, and stomach.
Conclusions

Data from our study indicate that abnormal glucose metabolism, independent of BMI, is associated with an increased risk of cancer overall and at several cancer sites. Our data showed stronger associations among women than among men, and for fatal cancer compared to incident cancer.

Please see later in the article for the Editors’ Summary

Citation: Stocks T, Rapp K, Bjørge T, Manjer J, Ulmer H, et al. (2009) Blood Glucose and Risk of Incident and Fatal Cancer in the Metabolic Syndrome and Cancer Project (Me-Can): Analysis of Six Prospective Cohorts. PLoS Med 6(12): e1000201. doi:10.1371/journal.pmed.1000201

Academic Editor: Nicholas J. Wareham, University of Cambridge Institute of Public Health, United Kingdom

Received: March 31, 2009; Accepted: November 10, 2009; Published: December 22, 2009

Copyright: © 2009 Stocks et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was supported by the World Cancer Research Fund (Grant 2007/09; website: www.wcrf.org/), and by the Swedish Cancer Society (Grant 2007/693; website: www.cancerfonden.se/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: 40-y, Age 40-programme; BMI, body mass index; CI, confidence interval; CONOR, Cohort of Norway; Me-Can, Metabolic syndrome and Cancer project; MPP, Malmö Preventive Project; NCS, Norwegian Counties Study; Oslo, Oslo study I; RDR, regression dilution ratio; RR, relative risk; SD, standard deviation; VHM&PP, Vorarlberg Health Monitoring and Prevention Programme; VIP, Västerbotten Intervention Project

Large prospective population-based research studies can have the power to discover new associations, and to verify previously proposed associations, between specific risk factors and the subsequent occurrence of disease. One such study, the “Me-Can” (Metabolic syndrome and Cancer project) is investigating associations between cancer incidence and a cluster of metabolic risk factors that make up metabolic syndrome: a large waistline; a high level of fats called triglycerides in the blood; a low level of “good” cholesterol; high blood pressure; and raised blood glucose (hyperglycemia). Here the researchers investigate the associations between one of these risk factors—raised blood glucose—and cancer. It is normal for blood glucose levels to vary before and after meals, but raised levels that persist long-term are known to lead to organ damage and severe complications. It is thought that more than 30% of cancer-related deaths could be prevented by modifying key risk factors, such as tobacco control, modifying diet, staying active, and limiting exposure to environmental risk factors.
Why Was This Study Done?

A previous large research study (including roughly 1.3 million men and women, conducted in Korea) has already evaluated the association between high blood glucose levels and cancer risk, and found that high blood glucose levels were linked with increased risk of cancer—both getting it and dying from it. Studies in European and US populations have also found a link, but they considered relatively small numbers of people and so these could not be used to calculate the risk with respect to specific cancer sites. The researchers carrying out the Me-Can project wanted to verify whether the associations reported in the Korean study also held true for European populations.
What Did the Researchers Do and Find?

The researchers identified 274,126 men and 275,818 women from existing health studies in Norway, Austria, and Sweden for whom data had been recorded on blood glucose level, height, and weight. For each participant a baseline measurement was defined, consisting of data from the first health examination, which had complete data (including a blood glucose measurement and whether the participant smoked). The participants were tracked via national registers for up to around 25 years after the baseline measurement but most commonly for around a decade. Any cancer diagnosis was recorded, whether the participant survived to the end of the study, and causes of death for participants who died during the study. The researchers analyzed the data to assess whether a higher blood glucose level was associated with increased risk of certain cancers, in both men and women. The researchers took weight for height, and smoking into account and adjusted for measurement error from additional blood glucose measurements. The researchers found that, overall, the higher the level of blood glucose, the higher the risk of getting and dying from cancer. Average normal blood glucose levels are about 5 mmol/l, also expressed as 5 mM or 90 mg/dl. For each additional 1 mmol/l increase in blood glucose level, the risk of getting cancer was increased by 5% for men and 11% for women.
What Do These Findings Mean?

The authors concluded that high blood glucose is associated with increased cancer risk. The results largely confirm findings from the Korean study, although there are some differences in the risks of cancers at some specific sites, which may be due to differences in the populations such as genetics, diet, and rates of smoking. Among the strengths of the study are its large sample size and that glucose were measured more than once for many individuals in the study. However, the study is limited in that the researchers did not have data on other possible factors such as genetics, physical activity, or dietary factors, which are linked to cancer incidence and also may be related to blood glucose levels. The researchers propose that controlling blood glucose may lower cancer risk in the population. Although this interpretation is consistent with the data, the study design cannot conclusively demonstrate a causal association between glucose levels and cancer risk.

Elevated blood glucose has been associated with an increased risk of cancer overall in several prospective studies [1]–[6]. The strongest evidence comes from a Korean cohort study of 1.3 million men and women that reported an increased risk of incident as well as of fatal cancer in individuals with high glucose levels [1]. Prospective studies of glucose and cancer risk in cohorts of European and US populations have been much smaller, and these studies did not concurrently report on risk of incident and fatal cancer [2]–[7]. Previous results from cohorts in Austria [2] and Sweden [3] included in the current study, also indicated that elevated fasting glucose is related to an increased risk of overall incident cancer. However, the relatively modest sample size in these studies resulted in limited power to estimate risks for individual cancer sites. Furthermore, exposure assessment by glucose measurement at a single occasion entails a substantial random error owing to technical measurement error and within-person variation of blood glucose level [8],[9]. Such inaccuracy of exposure assessment will dilute the association with outcome, i.e., regression dilution bias [8],[10],[11]. In several prospective studies of metabolic factors and risk of cardiovascular disease, data from multiple examinations have been used to correct risk estimates for random error in exposure classification, which resulted in substantially stronger associations than estimates on the basis of uncorrected exposures [12]–[14]. To date, correction for random error has only been performed in one study on glucose and cancer risk [3].

The aim of this study was to investigate the association between blood glucose and risk of incident and fatal cancer overall and at specific sites, as well as all-cause mortality, in a large study of six European cohorts including correction for random error in glucose levels.

Material and Methods Top
Me-Can

The Metabolic syndrome and Cancer project (Me-Can) includes data from population-based cohorts in Norway, Austria, and Sweden. A detailed description of Me-Can has recently been published [15]. In brief, the Norwegian cohorts includes the Oslo study I cohort (Oslo) [16],[17], the Norwegian Counties Study (NCS) [18],[19], the Cohort of Norway (CONOR) [20], and the Age 40-programme (40-y) [21]. The Austrian cohort consists of the Vorarlberg Health Monitoring and Prevention Programme (VHM&PP) [2], and the Swedish cohorts are the Västerbotten Intervention Project (VIP) [22], and the Malmö Preventive Project (MPP) [23],[24]. Written informed consent was obtained from all participants included in this study, and the study was approved by research ethical committees in the respective countries.

Data on height, weight, blood pressure, and blood, plasma, or serum levels of glucose, total cholesterol, and triglycerides had been collected at health examinations in all cohorts. Height and weight were measured in a similar way in all cohorts; without shoes and with light indoor clothing. In the Norwegian cohorts, fasting was not required before the examination, and fasting time was recorded as <1 h, 1–2, 2–4, 4–8, or >8 h. Fasting time in the VIP was recorded as <4 h, 4–8, or >8 h, and from 1992, participants were asked to fast for at least 8 h before the examination. In the MPP and after the initial 3 y in the VHM&PP, a minimum of 8 h fasting time before blood draw was implemented. Glucose levels were measured in the Oslo and the NCS in serum glucose with a nonenzymatic method; in CONOR and the 40-y cohort, serum/enzymatic; in the VHM&PP and the VIP, plasma/enzymatic; and in the MPP, whole blood/enzymatic. In the Norwegian cohorts, the nonenzymatic method used during the first study period yielded 0.8–1.1 mmol/l higher levels than by the use of an enzymatic method [25]. Data from several health examinations were available for a subset of individuals in some of the Me-Can cohorts [15], and for each person in the study, data from one health examination constituted the baseline observation, described as follows.
Follow-up and Selection of Participants

Each of the cohorts was linked to the respective national registers for identification of (a) cancer diagnosis, (b) migration, (c) vital status, and (d) cause of death, with death attributed to cancer if the underlying cause of death was cancer. Follow-up for each of the cohorts includes the year as follows: Norwegian cohorts, (a–c) 2005, (d) 2004; the VHM&PP, (a) 2003, (b) no information available, (c, d) 2003; the VIP and the MPP (a–c) 2006, (d) 2004.

Selection of individuals for the study is described in Figure 1. From the original data with 904,060 individuals and 1,600,296 observations, we excluded observations with: nonmatching data, a cancer diagnosis at or before the date of health examination, extreme values of metabolic factors [15] (<1 mmol/l for glucose and <15 or >60 kg/m2 for body mass index [BMI]), missing data for BMI, glucose or fasting time, a shorter time than 1 y between the date of examination and end of follow-up for cancer incidence, and observations in the VHM&PP that included data on postload glucose instead of fasting glucose. Out of the 574,356 excluded observations, 414,629 observations were excluded in the Norwegian cohorts in individuals for whom data on glucose were missing, as blood glucose had not been measured as a standard in these cohorts throughout all time-periods. From the remaining 611,459 individuals with 1,025,940 observations, we selected the first observation for each individual, and if data from a fasting state and data on smoking status were available, the first of these observations was selected. Thus, for each individual, data were included from the first health examination with complete data to comprise the baseline set of measurements. Due to policy restrictions imposed by the Norwegian Institute of Public Health that the proportion of Norwegian individuals in Me-Can studies should not exceed approximately 50% (56% after the above selection), we further excluded 1,868 individuals in Norway without data on smoking status, and the entire NCS cohort (n = 59,647). The reason for excluding an entire cohort was to keep the included Norwegian cohorts intact and to keep down the number of strata in statistical analyses, as a large number of strata reduce statistical power. We excluded the NCS cohort as it consisted of approximately the number of individuals that was required to be excluded. The final dataset included 549,944 individuals, 274,126 men and 275,818 women.
thumbnail

Categorisation of Cancers

Incident and fatal cancers, categorised according to the International Classification of Diseases, seventh revision (ICD-7) codes, were grouped into cancer sites as grouped in the Eurostat European shortlist for cause of death [26], which was used for cause of death classification in the Norwegian cohorts. Incident cancers were further divided into relevant subgroups. Relative risks (RR) for incident and fatal cancer at specific sites are presented separately for men and women if the number of cases in each group was >50, and risks are presented for men and women combined if the number of cases in each group was ≤50 and if the total number of cases was >80.
Statistical Analysis

In order to reduce the probability of reverse causation, rates, RRs and absolute risks were calculated with follow-up starting 1 y after the baseline examination. Individuals were followed until the date of event, i.e., cancer diagnosis or cancer death, or until the date of death from any cause, emigration, or end of follow-up, whichever occurred first. Rates were directly age-standardized in 5-y categories, using the European standard population as the reference [27]. We used Cox proportional hazards regression to calculate hazard ratios, denoted as RRs, for glucose levels with risk of incident and fatal cancer, and of death from all causes. Age was used as time variable and all estimates were stratified by subcohort, sex, and by categories of birth date: before 1923, 1923–1930, 1931–1938, 1939–1946, 1947–1954, 1955, and later. We estimated RR for glucose levels in quintiles and deciles, for which cut-off levels were calculated within each subcohort, sex, and category of fasting time. p for trend over quintiles and deciles refers to the p-value for the Wald test of a linear risk estimate, assigning participants included in each analysis the mean sex- and cohort-specific glucose level within the corresponding quantile. RR was also assessed for glucose as a continuous variable, i.e., per 1 mmol/l increment. In order to exclude outliers, these analyses were restricted to individuals with glucose levels lower than 10 mmol/l (99% of individuals). All analyses included adjustment for age at measurement (continuous), BMI (categories: <22.5, 22.5 to <25.0, 25.0 to <27.5, 27.5 to <30.0, 30.0 to <32.5 kg/m2) and smoking status (categories: never smoker, ex-smoker, current smoker, and unknown), and analyses of glucose as a continuous variable were also adjusted for fasting time.

We calculated regression dilution ratio (RDR) of glucose in order to adjust RRs for random error in glucose level [8],[10],[11]. RDR was calculated on the basis of data from repeated health examinations in 133,820 individuals, including 406,364 observations, in the full Me-Can cohort. Only repeated measurements with the same fasting time and in the same cohort as at baseline, and with data on smoking status, were used. However, as the same method for glucose measurement had been used in the Oslo and the NCS cohorts, and in the CONOR and 40-y cohorts, participants with measurements in the Oslo and in the NCS, or in CONOR and in the 40-y cohort, were included in analyses. Mean time between the baseline measurement and repeated measurements was 6.9 y (standard deviation [SD] = 3.9). We used a linear mixed effects model, similar to that described by Wood et al. [11], which included age at baseline, fasting time, smoking status, sex, and time from baseline as fixed effects, and cohort as random effect. RDR was estimated separately for men and women, and combined, in models for (a) glucose standardised within cohort, sex and fasting time, and for (b) glucose only including individuals with a baseline glucose level lower than 10 mmol/l. Model (a) was used to predict RDR among individuals in the current study with data on smoking status, for correction of RRs in quantiles, and model (b) was used to predict RDR among individuals with data on smoking status and with a glucose level lower than 10 mmol/l, for correction of RRs of per 1 mmol/l increment. RDR was predicted for the time point at 5 y after baseline measurement, i.e., half the follow-up time [8],[10],[11]. We used the mean of predicted RDRs for correction of RR, which resulted in RDRs for quantile analyses of: 0.30 among men, 0.30 among women, and 0.31 overall, and in analyses of per 1 mmol/l increment: 0.40 among men, 0.43 among women, and 0.41 overall. Correction of RRs for RDR was obtained by exp(log(RR)/RDR), using the sex-specific RDR in analyses that included men or women only, and using the combined RDR in analyses that included both sexes.

Cox proportional hazards assumption was checked for glucose and covariates by the statistical test of Schoenfeld residuals. For some cancers, there was an indication of violation of proportionality for BMI or smoking status, but as RRs were very similar with and without stratification of the variable within the model, BMI and smoking status were not kept as stratum in the final model. For a few cancers there was an indication of violation of the proportionality over age for glucose; however, we report RRs only in the full study group and not in subgroups of age. Interaction between glucose and (a) BMI, (b) fasting time, and (c) cohort on the risk of overall incident and fatal cancer was checked by analysing RRs in subgroups of BMI, fasting time, and cohort, and by performing likelihood ratio tests comparing the model used to assess RR per 1 mmol/l increment with a model that additionally included a product term of continuous glucose and categories of BMI, fasting time, or cohort, respectively. Interaction between glucose and fasting time was assessed in the Norwegian cohorts. Evidence of a nonlinear association between glucose and risk of overall incident and fatal cancer was tested by likelihood ratio test, comparing the model with glucose as a continuous variable with a model that also included an x2 term of glucose. In order to assess linearity across the whole glucose range, all individuals were included in this analysis. Absolute risks of incident and fatal cancer between 50 and 70 y of age were calculated as described by Gail et al. [28]. For this method, risk of cancer and of dying from other causes than cancer was derived from the cohort for ages 50 to 60 y and 60 to 70 y, respectively. Statistical analyses were performed in Stata (version 9.2, StataCorp LP), and R (version 2.7.2, used for RDR calculation).

Baseline Characteristics and Follow-up

Mean age at baseline was 44.7 y (SD = 11.6) in men and 45.0 y (SD = 12.8) in women (Table 1). The prevalence of overweight or obesity, i.e., BMI 25 kg/m2 or higher, was 56% among men and 42% among women. All participants in the VHM&PP and the MPP and 90% of participants in the VIP had fasted >8 h before the health examination, whereas 95% of participants in the Norwegian cohorts had fasted <8 h. Among individuals that had fasted >8 h, 8% of men and 6% of women had impaired glucose levels according to the World Health Organization definition [29] (6.1–6.9 mmol/l in serum/plasma or 5.6–6.0 mmol/l in whole blood), and 4% of men and 3% of women had diabetic glucose levels (≥7.0 mmol/l in serum/plasma or ≥6.1 mmol/l in whole blood). Baseline age and BMI increased for each increment of glucose quintile (Table 2).
thumbnail

Table 1. Baseline characteristics of study individuals in Me-Can.
doi:10.1371/journal.pmed.1000201.t001
thumbnail

Table 2. Characteristics of individuals within quintile levels of glucose.
doi:10.1371/journal.pmed.1000201.t002

The mean follow-up time was 11.3 y (SD = 7.4) in men and 9.6 y (SD = 4.4) in women. Excluding the first year of observation, 18,621 men and 11,664 women were diagnosed with cancer during follow-up and 6,973 men and 3,088 women died of cancer.
Glucose and RR of Cancer

Glucose was significantly positively associated with risk of overall incident and fatal cancer. In men, the RR (95% confidence interval [CI]) per 1 mmol/l increment was for incident cancer 1.05 (1.01–1.10), and for fatal cancer 1.15 (1.07–1.22) (Tables 3 and 4). In analysis of glucose in quintiles, the RR for the top versus bottom quintile was for incident cancer 1.18 (1.00–1.37, p for trend = 0.06), and for fatal cancer 1.50 (1.18–1.94, p for trend<0.001). Significant increases in risk of incident and fatal cancer at specific sites per 1 mmol/l increment in glucose among men were observed for cancer of the liver, gallbladder, and the respiratory tract. Significant linear associations were also found for incident thyroid cancer, multiple myeloma, and for fatal rectal cancer, and glucose in the top quintile was associated with a significant increased risk of fatal colon cancer.
thumbnail

Table 3. RR of incident cancer by glucose in quintiles and per 1 mmol/l increment.
doi:10.1371/journal.pmed.1000201.t003
thumbnail

Table 4. RR of overall death and of fatal cancer by glucose in quintiles and per 1 mmol/l increment.
doi:10.1371/journal.pmed.1000201.t004

In women, the association between a 1 mmol/l increase in glucose level and overall cancer was somewhat stronger than in men; the RR among women for incident cancer was 1.11 (1.05–1.16), and for fatal cancer 1.21 (1.11–1.33) (Tables 3 and 4). Significant positive associations among women were observed for incident and fatal cancer of the pancreas, and stomach (borderline significant for incidence). A significant linear association was also observed for incident urinary bladder cancer and for fatal cervix and uterine corpus cancer. Furthermore, top quintile level of glucose was significantly associated with an increased risk of incident endometrial cancer, and a decreased risk of incident thyroid cancer.

In men and women combined, a 1 mmol/l increment in glucose level was associated with an increased risk of death from cancer of the oropharynx and oesophagus.

BMI and fasting time before blood draw had no effect on the association between glucose and risk of cancer overall in men or in women (p for interaction, all >0.05). There was no significant interaction between glucose and subcohort on the risk of incident and fatal cancer in men, or for fatal cancer in women (p for interaction, all >0.05). However, the association between glucose and risk of incident cancer in women differed significantly between the cohorts; the overall p-value for interaction was 0.02, and the RR per 1 mmol/l increment of glucose ranged between 0.98 (0.84–1.12) in the 40-y cohort, and 1.30 (1.15–1.50) in the VIP. No similar pattern was observed in men, among whom the RR for incident cancer was lowest in the VIP (RR = 0.95) and highest in the VHM&PP.
Decile Levels of Glucose and Risk

We further explored risk of cancer by decile categories of glucose levels. In order to use a broad referent category that includes healthy normal glucose levels, we used the lowest 40% of glucose levels as referent group. Among fasting individuals, the cut-off for impaired fasting glucose was in the top 10%–20% of glucose levels. The association between glucose level and cancer risk was approximately linear across the full range of glucose levels (Figures 2 and 3), and the extension of a linear model with an x2 variable did not significantly improve the fit of the association with incident or fatal cancer among men or women (p, all >0.05). In men, the RR for top decile versus decile 1–4 for incident cancer was 1.14 (0.97–1.33, p for trend = 0.09), and for fatal cancer 1.84 (1.46–2.40, p for trend<0.001). RRs of total cancer, excluding prostate cancer, were for incident cancer 1.37 (1.14–1.64, p for trend = 0.002), and for fatal cancer 2.10 (1.59–2.72, p for trend<0.001). In women, the RR for top decile versus decile 1–4 for overall incident cancer was 1.42 (1.18–1.74, p for trend<0.001), and for fatal cancer 2.05 (1.42–2.93, p for trend<0.001). The corresponding RR for overall death was in men 3.29 (2.86–3.78, p for trend<0.001), and in women 3.69 (3.00–4.59, p for trend<0.001).
thumbnail

Figure 2. RR (95% CI) in men of incident (n = 18,621) and fatal (n = 6,973) cancer by deciles of glucose.

The risk estimates for decile categories are plotted on the x-axis at the mean glucose level for each decile category. IFG indicates the range of impaired fasting glucose in the cohorts among individuals that had fasted more than 8 h before the blood draw, and DM indicates the range of diabetic glucose levels. Glucose levels in the Oslo study I were recalculated (level −0.95) to correspond with enzymatic levels.
doi:10.1371/journal.pmed.1000201.g002
thumbnail

Figure 3. RR (95% CI) in women of incident (n = 11,664) and fatal (n = 3,088) cancer by deciles of glucose.

The risk estimates for decile categories are plotted on the x-axis at the mean glucose level for each decile category. IFG indicates the range of impaired fasting glucose in the cohorts among individuals that had fasted more than 8 h before the blood draw, and DM indicates the range of diabetic glucose levels.
doi:10.1371/journal.pmed.1000201.g003

The absolute risk of incident cancer over a 20-y period for a 50-y old man in decile 1–4 and decile 10 of glucose was 14.0% and 15.7%, respectively, and the corresponding risk of fatal cancer was 5.0% and 8.8%. In women, the corresponding absolute risks of developing cancer were 12.2% and 16.7%, and for cancer death, 3.0% and 6.0%, respectively.

In this large prospective cohort study, elevated blood glucose was significantly associated with an increased risk of incident and fatal cancer at all sites combined, and of several specific cancers. In women, a linear association between glucose and risk of overall incident and fatal cancer was observed, and levels within the upper normal range were also related to increases in risk. In men, the association between glucose and total incident cancer was somewhat weaker, and risk of fatal cancer was only significantly increased at levels approximately equivalent to impaired glucose levels. Women in the top glucose decile had twice the risk of fatal cancer compared to women with glucose levels below the 40th percentile and the risk increase among men in the top decile was almost the same. Risk estimates were obtained after correction for random error in glucose levels, which was high in our study in accordance with previous observations [3],[8],[9]. The estimates of excess risk of fatal cancer in the top decile corrected for regression dilution were 4-fold higher than the uncorrected estimates. These data indicate that in previous analyses without such correction, risk estimates for increasing glucose may have been underestimated [1]–[7].

Results from our study and those from the largest study reported to date, on men and women in Korea [1], were largely congruent and together these studies provide strong evidence that high blood glucose is a risk factor for cancer. In our study, associations between glucose and overall incident and fatal cancer were stronger in women than in men, whereas in the Korean study, stronger associations were reported for men, for whom a significant increased risk of fatal cancer was observed already at levels below impaired fasting glucose. These differences between studies may be explained by different proportions of specific cancers in the populations. For example, prostate cancer is much more common in Europe than in Asia [30], and as glucose was not related to prostate cancer in either study, exclusion of prostate cancer in analyses of total cancer in our study strengthened the association with cancer. Type 2 diabetes has consistently been related to an increased risk of cancer at many sites [1],[31]–[33], and the findings in our and the Korean study suggest also that impaired fasting glucose levels, and to a lesser extent, also glucose levels within the upper normal range are associated with an increased risk of cancer.

Specific cancers for which there were strong associations between glucose and risk of incident and fatal cancer in the Korean study [1] and in our study, were pancreatic cancer, particularly in women, and liver cancer in men. Moreover, both studies showed strong associations between elevated glucose and risk of fatal cancer of the oesophagus and cervix uteri, and of fatal colorectal cancer in men. In our study, elevated glucose was also associated with an increased risk of cancer of the respiratory tract in men, and of gastric cancer in women, whereas no such associations were found in the Korean study. Smoking is strongly related to lung cancer and gastric cancer [34], and confounding or interaction between glucose and smoking may possibly explain the divergent findings. The proportion of current smokers in men was 29% in our study and 59% in the Korean study, and corresponding proportions were 23% and 4% in women. We observed no confounding or effect modification by smoking status in analyses of these cancers, but residual confounding may be present owing to an imprecise or incorrect categorisation of smoking status.

Our study is the first to report data on glucose and risk of oropharyngeal cancer, and suggests an increased risk of death from these cancers in individuals with elevated glucose. Furthermore, data on prediagnostic glucose levels and risk of multiple myeloma and thyroid cancer have previously been reported only from the VHM&PP cohort [2]. We found a significant increase in risk of these cancers in men with high glucose, whereas intriguingly, risk of thyroid cancer was markedly decreased in women with high glucose. Incidence rates of thyroid cancer are 2–3 times higher in women than in men, possibly influenced by female sex hormones [35]–[37], and we speculate that an interaction between sex hormones and glucose may underlie our findings, alternatively the results may be a chance finding.

Insulin and bioavailable insulin-like growth factor-I (IGF-I) are possible links between glucose and cancer; hyperglycaemia induces elevation of these hormones that stimulate tumour growth [38]. Glucose may also have a direct tumour-promoting effect as glucose is used as an energy substrate in tumour cells, particularly in fast-growing, highly proliferative tumour cells [39]–[41]. However, the importance of extracellular glucose concentration for tumour growth—and thereby a direct link between glucose itself and cancer risk—is unclear.

Although the link between glucose and cancer may be causal, confounding may also be involved. We controlled for two major putative confounders, BMI and smoking, and found that the association between glucose and cancer risk remained after adjustment for these factors. However, other putative confounding factors may be relevant. For example, a genetic variant with opposite effects on risk of type 2 diabetes and prostate cancer has recently been reported [42], and this could partly explain the null association between glucose and prostate cancer in our study as well as the consistently reported reduced risk of prostate cancer in men with type 2 diabetes [43]. Various lifestyle factors, related to glucose but with other pathways to cancer, are also potential confounders, e.g., alcohol for cancer of the oropharynx, oesophagus, liver, and colorectum, salt for gastric cancer, and physical activity and fruit and vegetable consumption for a number of cancers [44].

The association between glucose and cancer risk was stronger for fatal cancer overall and at several sites than for incident cancer. The explanation for this difference may vary between cancer types. Possibly, high glucose and related factors are more important for tumour progression than for tumour initiation. Alternatively, persons with high glucose may be diagnosed with cancer at a later stage, e.g., because of different health care seeking behaviour, or the results may be caused by inconsistencies in classification of cancer diagnosis versus cause of death [45],[46].

Previous studies have consistently shown an association between elevated glucose levels and risk of cardiovascular disease and also to all cause mortality [1],[47]–[49]. Accordingly, we found that elevated glucose was strongly related to an increased risk of all cause mortality; glucose levels in the top decile were related to a more than 3-fold increased risk. Our data indicate that glucose control by a healthy diet and physical activity may decrease risk of cancer at many sites in addition to a decreased risk of cardiovascular disease.

Strengths of our study include the large sample size from six European population-based cohorts with virtually complete capture of cancer cases [2],[50],[51], the use of incident as well as fatal cancer as endpoints, and the correction of risk estimates for intra-individual variation of glucose levels based on a large number of repeated measurements. In all cohorts, data were available for BMI and smoking status, and these factors were used as adjustment in analyses. Limitations of our study include the lack of data on other covariates that may have influenced risk estimates, and the different protocols for measurement of glucose applied in subcohorts, which invalidated the use of absolute glucose levels to our data.

In conclusion, abnormal glucose metabolism, independent of BMI, is associated with increases in risk of cancer and cancer death overall and at many specific sites. Furthermore, our data showed a linear and somewhat stronger association among women than among men, and the association was stronger for fatal compared to incident cancer.

We thank: in Norway, the screening team at the former National Health Screening Service of Norway, now the Norwegian Institute of Public Health, the contributing research centres delivering data to CONOR; in the VHM&PP, Elmar Stimpfl, data base manager, Karin Parschalk at the cancer registry, and Elmar Bechter and Hans-Peter Bischof, medical doctors at the Health Department of the Vorarlberg State Government; in the VIP, Åsa Ågren, project data base manager at the Medical Biobank, Umeå University, Sweden; and in the MPP, Anders Dahlin, data base manager. We also thank Angela Wood, statistician at the Department of Public Health and Primary Care, University of Cambridge, United Kingdom, and Ove Björ, statistician at the Oncological centre, Umeå University, Sweden, for advice on statistical analyses.

ICMJE criteria for authorship read and met: TS KR TB JM HU RS AL DJ HC ST GH HJ PS. Agree with the manuscript’s results and conclusions: TS KR TB JM HU RS AL DJ HC ST GH HJ PS. Designed the experiments/the study: TS TB JM HU PS. Analyzed the data: TS TB JM HU DJ HJ PS. Collected data/did experiments for the study: HC GH HJ. Enrolled participants: HC GH. Wrote the first draft of the paper: TS PS. Contributed to the writing of the paper: TS KR TB JM HU RS AL ST GH HJ PS. Responsible for integrity of the Norwegian data: RS. Responsible for the linkage and the quality of the dataset and for ensuring that the application of the data is correct: for Norwegian data, ST; for the full Me-Can cohort, TS, HJ. Principal investigator of the Me-Can project; designed and financed the Me-Can project as well as the specific study on glucose and cancer risk: PS.

1. Jee SH, Ohrr H, Sull JW, Yun JE, Ji M, et al. (2005) Fasting serum glucose level and cancer risk in Korean men and women. JAMA 293: 194–202. Find this article online
2. Rapp K, Schroeder J, Klenk J, Ulmer H, Concin H, et al. (2006) Fasting blood glucose and cancer risk in a cohort of more than 140,000 adults in Austria. Diabetologia 49: 945–952. Find this article online
3. Stattin P, Bjor O, Ferrari P, Lukanova A, Lenner P, et al. (2007) Prospective study of hyperglycemia and cancer risk. Diabetes Care 30: 561–567. Find this article online
4. Tulinius H, Sigfusson N, Sigvaldason H, Bjarnadottir K, Tryggvadottir L (1997) Risk factors for malignant diseases: a cohort study on a population of 22,946 Icelanders. Cancer Epidemiol Biomarkers Prev 6: 863–873. Find this article online
5. Levine W, Dyer AR, Shekelle RB, Schoenberger JA, Stamler J (1990) Post-load plasma glucose and cancer mortality in middle-aged men and women. 12-year follow-up findings of the Chicago Heart Association Detection Project in Industry. Am J Epidemiol 131: 254–262. Find this article online
6. Saydah SH, Loria CM, Eberhardt MS, Brancati FL (2003) Abnormal glucose tolerance and the risk of cancer death in the United States. Am J Epidemiol 157: 1092–1100. Find this article online
7. Smith GD, Egger M, Shipley MJ, Marmot MG (1992) Post-challenge glucose concentration, impaired glucose tolerance, diabetes, and cancer mortality in men. Am J Epidemiol 136: 1110–1114. Find this article online
8. Emberson JR, Whincup PH, Morris RW, Walker M, Lowe GD, et al. (2004) Extent of regression dilution for established and novel coronary risk factors: results from the British Regional Heart Study. Eur J Cardiovasc Prev Rehabil 11: 125–134. Find this article online
9. Whitlock G, Clark T, Vander Hoorn S, Rodgers A, Jackson R, et al. (2001) Random errors in the measurement of 10 cardiovascular risk factors. Eur J Epidemiol 17: 907–909. Find this article online
10. Clarke R, Shipley M, Lewington S, Youngman L, Collins R, et al. (1999) Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol 150: 341–353. Find this article online
11. Wood AM, White I, Thompson SG, Lewington S, Danesh J (2006) Regression dilution methods for meta-analysis: assessing long-term variability in plasma fibrinogen among 27,247 adults in 15 prospective studies. Int J Epidemiol 35: 1570–1578. Find this article online
12. MacMahon S, Peto R, Cutler J, Collins R, Sorlie P, et al. (1990) Blood pressure, stroke, and coronary heart disease. Part 1, prolonged differences in blood pressure: prospective observational studies corrected for the regression dilution bias. Lancet 335: 765–774. Find this article online
13. Danesh J, Kaptoge S, Mann AG, Sarwar N, Wood A, et al. (2008) Long-term interleukin-6 levels and subsequent risk of coronary heart disease: two new prospective studies and a systematic review. PLoS Med 5: e78. doi:10.1371/journal.pmed.0050078.
14. Freiberg JJ, Tybjaerg-Hansen A, Jensen JS, Nordestgaard BG (2008) Nonfasting triglycerides and risk of ischemic stroke in the general population. JAMA 300: 2142–2152. Find this article online
15. Stocks T, Borena W, Strohmaier S, Bjorge T, Manjer J, et al. (2009) Cohort Profile: The Metabolic syndrome and Cancer project (Me-Can). Int J Epidemiol. In press. Find this article online
16. Leren P, Askevold EM, Foss OP, Froili A, Grymyr D, et al. (1975) The Oslo study. Cardiovascular disease in middle-aged and young Oslo men. Acta Med Scand Suppl 588: 1–38. Find this article online
17. Lund Haheim L, Wisloff TF, Holme I, Nafstad P (2006) Metabolic syndrome predicts prostate cancer in a cohort of middle-aged Norwegian men followed for 27 years. Am J Epidemiol 164: 769–774. Find this article online
18. Bjartveit K, Foss OP, Gjervig T (1983) The cardiovascular disease study in Norwegian counties. Results from first screening. Acta Med Scand Suppl 675: 1–184. Find this article online
19. Tverdal A, Foss OP, Leren P, Holme I, Lund-Larsen PG, et al. (1989) Serum triglycerides as an independent risk factor for death from coronary heart disease in middle-aged Norwegian men. Am J Epidemiol 129: 458–465. Find this article online
20. Naess O, Sogaard AJ, Arnesen E, Beckstrom AC, Bjertness E, et al. (2008) Cohort profile: cohort of Norway (CONOR). Int J Epidemiol 37: 481–485. Find this article online
21. Aires N, Selmer R, Thelle D (2003) The validity of self-reported leisure time physical activity, and its relationship to serum cholesterol, blood pressure and body mass index. A population based study of 332,182 men and women aged 40–42 years. Eur J Epidemiol 18: 479–485. Find this article online
22. Lindahl B, Weinehall L, Asplund K, Hallmans G (1999) Screening for impaired glucose tolerance. Results from a population-based study in 21,057 individuals. Diabetes Care 22: 1988–1992. Find this article online
23. Berglund G, Eriksson KF, Israelsson B, Kjellstrom T, Lindgarde F, et al. (1996) Cardiovascular risk groups and mortality in an urban Swedish male population: the Malmo Preventive Project. J Intern Med 239: 489–497. Find this article online
24. Berglund G, Nilsson P, Eriksson KF, Nilsson JA, Hedblad B, et al. (2000) Long-term outcome of the Malmo preventive project: mortality and cardiovascular morbidity. J Intern Med 247: 19–29. Find this article online
25. Bjartveit K, Foss OP, Gjervig T, Lund-Larsen PG (1979) The cardiovascular disease study in Norwegian counties. Background and organization. Acta Med Scand Suppl 634: 1–70. Find this article online
26. Eurostat (1998) European shortlist for causes of death, 1998. Available: http://ec.europa.eu/eurostat/ramon/nomen​clatures/index.cfm?TargetUrl=LST_NOM_DTL​&StrNom=COD_1998 . Accessed 1 December 2008.
27. Doll R, Cook P (1967) Summarizing indices for comparison of cancer incidence data. Int J Cancer 2: 269–279. Find this article online
28. Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, et al. (1989) Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 81: 1879–1886. Find this article online
29. World Health Organisation (1999) Definition, diagnosis and classification of diabetes mellitus and its complications. Report of a WHO consultation. Part 1: Diagnosis and classification of diabetes mellitus. Geneva: World Health Organisation.
30. Boyle P, Levin B (2008) World Cancer Report 2008. Lyon: International Agency for Research on Cancer (IARC).
31. Strickler HD, Wylie-Rosett J, Rohan T, Hoover DR, Smoller S, et al. (2001) The relation of type 2 diabetes and cancer. Diabetes Technol Ther 3: 263–274. Find this article online
32. Wideroff L, Gridley G, Mellemkjaer L, Chow WH, Linet M, et al. (1997) Cancer incidence in a population-based cohort of patients hospitalized with diabetes mellitus in Denmark. J Natl Cancer Inst 89: 1360–1365. Find this article online
33. Coughlin SS, Calle EE, Teras LR, Petrelli J, Thun MJ (2004) Diabetes mellitus as a predictor of cancer mortality in a large cohort of US adults. Am J Epidemiol 159: 1160–1167. Find this article online
34. Sasco AJ, Secretan MB, Straif K (2004) Tobacco smoking and cancer: a brief review of recent epidemiological evidence. Lung Cancer 45: Suppl 2S3–9. Find this article online
35. Preston-Martin S, Franceschi S, Ron E, Negri E (2003) Thyroid cancer pooled analysis from 14 case-control studies: what have we learned? Cancer Causes Control 14: 787–789. Find this article online
36. Negri E, Dal Maso L, Ron E, La Vecchia C, Mark SD, et al. (1999) A pooled analysis of case-control studies of thyroid cancer. II. Menstrual and reproductive factors. Cancer Causes Control 10: 143–155. Find this article online
37. La Vecchia C, Ron E, Franceschi S, Dal Maso L, Mark SD, et al. (1999) A pooled analysis of case-control studies of thyroid cancer. III. Oral contraceptives, menopausal replacement therapy and other female hormones. Cancer Causes Control 10: 157–166. Find this article online
38. Dossus L, Kaaks R (2008) Nutrition, metabolic factors and cancer risk. Best Pract Res Clin Endocrinol Metab 22: 551–571. Find this article online
39. Warburg O (1956) On the origin of cancer cells. Science 123: 309–314. Find this article online
40. Airley RE, Mobasheri A (2007) Hypoxic regulation of glucose transport, anaerobic metabolism and angiogenesis in cancer: novel pathways and targets for anticancer therapeutics. Chemotherapy 53: 233–256. Find this article online
41. Moreno-Sanchez R, Rodriguez-Enriquez S, Marin-Hernandez A, Saavedra E (2007) Energy metabolism in tumor cells. FEBS J 274: 1393–1418. Find this article online
42. Gudmundsson J, Sulem P, Steinthorsdottir V, Bergthorsson JT, Thorleifsson G, et al. (2007) Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes. Nat Genet 39: 977–983. Find this article online
43. Kasper JS, Giovannucci E (2006) A meta-analysis of diabetes mellitus and the risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 15: 2056–2062. Find this article online
44. World Cancer Research Fund/American Institute for Cancer Research (2007) Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Washington (D.C.): AICR.
45. Johansson LA, Westerling R (2000) Comparing Swedish hospital discharge records with death certificates: implications for mortality statistics. Int J Epidemiol 29: 495–502. Find this article online
46. Johansson LA, Westerling R (2002) Comparing hospital discharge records with death certificates: can the differences be explained? J Epidemiol Community Health 56: 301–308. Find this article online
47. Barr EL, Zimmet PZ, Welborn TA, Jolley D, Magliano DJ, et al. (2007) Risk of cardiovascular and all-cause mortality in individuals with diabetes mellitus, impaired fasting glucose, and impaired glucose tolerance: the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab). Circulation 116: 151–157. Find this article online
48. The DECODE study group (2001) Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med 161: 397–405. Find this article online
49. Nakagami T (2004) Hyperglycaemia and mortality from all causes and from cardiovascular disease in five populations of Asian origin. Diabetologia 47: 385–394. Find this article online
50. Cancer Registry of Norway (2006) Cancer in Norway 2006. Available: http://www.kreftregisteret.no/no/Generel​t/Publikasjoner/Cancer-in-Norway/Cancer-​in-Norway-2006/ . Accessed 1 December, 2008.
51. Barlow L, Westergren K, Holmberg L, Talback M (2008) The completeness of the Swedish Cancer Register – a sample survey for year 1998. Acta Oncol 1–7.