By Matt Wood

In a recent column in the New York Times, Nick Kristof pointed out a startling statistic: for every American soldier killed in combat this year, 25 will commit suicide. A report from the Center for a New American Security says that from 2005 to 2010, service members took their own lives at a rate of one every 36 hours, and the Department of Veterans Affairs says that 18 veterans commit suicide every day.

Further analysis of this epidemic uncovers even more troublesome data. In a recent study published in the American Journal of Public Health, a statistician from the University of Chicago Center for Health Statistics found that the youngest group of veterans, ages 17-24, were almost four times as likely to commit suicide than nonveterans.

Robert Gibbons, PhD, professor of biostatistics in the departments of Medicine and Health Studies has long been interested in statistical analysis of suicide data to uncover patterns that could point to potential intervention strategies and treatment policies. He was on the Food and Drug Administration (FDA) committee in 2004 that issued a “black box warning” about increased suicide risk in children taking antidepressants. He actually voted against the warning, citing concerns about ambiguous data, and earlier this year published his own statistical analysis of the clinical trials the FDA used for their warning and found that the drugs were quite effective in decreasing suicide risk in adults and neither increased nor decreased suicide risk in children and adolescents.

In his current work on veteran suicide, Gibbons and his colleagues tackled another statistical disagreement. The editors of the American Journal of Public Health asked him to write an editorial about two studies on the rate of suicide among veterans that showed conflicting results. He and his colleagues weren’t able to replicate the results of either study, so they decided to do their own using publicly available data.

“We realized there was just no way we were going to be able to be Solomon-like and opine about who was right or wrong,” Gibbons said. “So we decided to see if we could figure out a way to shed some light on the answer using stuff off the internet, something a 10-year-old could get.”

Those data are from the Centers for Disease Control and Prevention National Violent Death Reporting System, which provides detailed data on all violent deaths, including suicides, from 16 states from 2005 to 2008.

“It’s a very important data source that very few people know about or use, so we’re really happy to use it. It’s a great national resource,” Gibbons said. “I think what’s cool about it is that it shows you can actually learn something from data that are completely publicly available, and learn something that is probably right.”

The key difference in how Gibbons and his colleagues analyzed the data versus the two previous studies is that they looked at how the rate of suicide changed with age. Statistical analysis of epidemiological data commonly controls for age, but a more detailed stratification by age is required to tease out the effects of recent military service and the associated emotional and psychological traumas of war.

The problem with the two conflicting earlier reports was that they were based on national surveys that did not control for the time at which the veterans actively served in the military.  One study included veterans with more recent military service and identified an increased risk of suicide risk. The other study looked at veterans further removed from military service and did not find an effect.  Gibbons and his colleagues explained these differing conclusions in the editorial using their new results.

“The bottom line as it turns out there’s a really big risk of increased suicide right when you get out of your military service,” Gibbons said. The risk of suicide in the youngest group of veterans was almost four times higher than nonveterans. That number drops off after the age of 24, but remains around one and a half times higher.

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By Rob Mitchum

Arsenic is a deadly toxin, but it’s not one dose fits all. Two people exposed to the same level of the chemical can have entirely different responses, with Patient A developing the skin lesions, cancers, and respiratory conditions that are a hallmark of arsenic toxicity, while Patient B is entirely unaffected. Currently, no test exists to tell in advance who might be more vulnerable to the effects of arsenic, but scientists suspect that some clues may lie in a person’s genes. In the latest paper from Habibul Ahsan’s massive study of arsenic exposure in Bangladesh, researchers uncovered a promising genetic story that could help identify people at higher risk — and potentially help protect them from toxicity.

As discussed before on ScienceLife, Ahsan’s two studies in Bangladesh follow the victims of an almost unfathomable mass poisoning event. In the 1970’s, an international effort was put together to switch millions of Bangladeshis from disease-ridden water sources to well-water. Unfortunately, the groundwater tapped by those wells turned out to contain very high levels of arsenic…a dark fact that wasn’t discovered until some 20 years after their installation. Over those decades, some 77 million people in the country were drinking water containing arsenic concentrations as high as 27 times safe limits.

For more than a decade, Ahsan has studied the epidemiology of that long-term exposure in some 20,000 volunteers, as well as low-priced interventions to try to reduce toxicity. In his latest paper, published last week in PLoS Genetics, Ahsan’s team zoomed in on the DNA of those subjects, looking for genetic variants that predict higher arsenic toxicity in a pool of 3,000 Bangladeshi citizens from the larger studies. Using the methods of genome-wide association studies (GWAS) — one of the first such studies conducted in the developing world — the researchers found a genetic region that offers a promising and refreshingly logical story about what creates individual differences in vulnerability to arsenic.

“These results add clarity to the genetic architecture that is playing a role in arsenic toxicity and its underlying biology,” said Ahsan, Louis Block Professor of health studies, medicine and human genetics at the University of Chicago Medicine. “It’s a rare type of study for a major problem affecting millions of people around the world, and it opens up opportunities for genetic studies of other major public health problems in developing countries.”

Led by Ahsan and Brandon Pierce, assistant professor of epidemiology at the University of Chicago Medicine, the team looked for potential genetic influences on phenotypes such as arsenic metabolism and the risk of acquiring arsenic-induced skin lesions. After ingestion, the body metabolizes inorganic arsenic into first monomethylarsonic acid (MMA) and then dimethylarsinic acid (DMA). MMA is considered to be more toxic, while DMA is water-soluble and more easily excreted. Higher levels of DMA or lower levels of MMA measured from an individual’s urine are associated with lower toxicity.

A GWAS search for variants associated with high or low DMA/MMA ratios turned up several candidates in the region of a likely suspect gene: arsenite methyltransferase (As3MT), an enzyme known to be involved in arsenic metabolism. A second GWAS that compared subjects who suffered skin lesions after arsenic versus subjects who did not pointed to variants in the same region, offering more evidence for the gene’s involvement and a rare straightforward result for a genomic study.

“This makes perfect sense,” Ahsan said. “It gives us a very coherent story that we can now investigate in relation to other arsenic pathologies and in relation to a wide range of arsenic doses in this population. Many genomic signals that we see are not robust enough or do not pertain to a large population. But in this study, that is not the case. The finding is robust, and the impact is massive.”

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By Rob Mitchum

In 2004, the Food and Drug Administration placed their equivalent of a scarlet letter on the antidepressant fluoxetine. Acting on the compiled results of several clinical trials, the FDA affixed its foreboding “black box warning” on to the drug best known as Prozac, preaching caution about increased suicide risk in children and young adults who take the medication. The decision made headlines around the world, leading to similar warnings in other countries and widespread decreases in the amount of prescriptions issued for the drugs to both pediatric and adult patients.

The FDA’s decision, voted on by a 23-member scientific advisory panel, was not unanimous, passing 15-8. One of the panel’s dissenters was Robert Gibbons, a health statistician then at UIC who later joined the University of Chicago Medicine in 2010. Gibbons thought that the studies used by the FDA, based largely upon retrospective data and adverse event reports, left too much room for alternative explanations.

“I didn’t find the data compelling,” Gibbons said. “For example, kids randomized to drugs would have more side effects, more contact with their doctor, and would have more opportunity to talk about suicidal thoughts.”

Despite Gibbons’ misgivings, there wasn’t an alternative data set to replicate or dispute the conclusions of the FDA’s meta-analysis. But earlier this week, Gibbons and a group of collaborators published their own statistical analysis of the clinical trials assessing the relationship between antidepressants and suicide risk in Archives of General Psychiatry…and reached a very different conclusion.

The new analysis used longitudinal data collected in 40 pharmaceutical company clinical trials and one large NIH study of antidepressants in adults, senior citizens, and children. Instead of measuring suicide risk through reports of adverse events, these data sets contained the results of weekly planned assessments for each patient on a psychiatric scale that measures depressive and suicidal thoughts — allowing researchers to trace week-by-week the effects of drug vs. placebo on the symptoms.

Adult and geriatric clinical trials for two different antidepressant drugs, fluoxetine and venlafaxine, were analyzed, and both medications were found effective in reducing suicide risk and depression symptoms. Furthermore, the two effects were also found to be statistically associated, suggesting that the drugs reduced suicidal thoughts and behavior by alleviating depression. Therefore, Gibbons said, effective treatment of major depressive disorder and careful monitoring that the drug is actually working are both important for a patient’s safety.

“Basically, the results say that the mechanism by which the antidepressants affect suicide rates is by decreasing depression,” Gibbons said. “It follows that if a treatment is not working for an individual, the risk for suicidal behavior and perhaps worse remains high.”

The four pediatric trials included in the new analysis, which all tested fluoxetine, offered more mixed results. A significant reduction in depression symptoms was found across the four studies, suggesting that the drugs were working on their primary aim. But instead of supporting the justification for the black box warning, the new analysis found that the antidepressant did not increase suicidal thoughts and behaviors in children. Nor, however, did the antidepressant decrease suicidality in the population, suggesting that the riddle is not completely solved.

“I think that this paper supports the general idea that the effects of antidepressants in kids and adults are not really the same,” Gibbons said. “In kids, we don’t see a harmful effect, but we do see a disassociation between the beneficial effects on depression and the potential beneficial effect on suicide. Maybe children think about suicide in part because of depression, but also maybe due to other reasons not related to depression that are not affected by antidepressants.”

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As another year comes to a close we’d like to look back at the fascinating research breakthroughs and inspiring patient stories from 2011. ScienceLife ran 168 posts this year, and while we wish we could highlight all of them, here are a handful of our favorites from each month.

January

Patrick Wilson found out that the H1N1 virus could end up helping us fight all types of flu. Stephen Pruett-Jones studied how some male birds mimic the sounds of predators to pick up the ladies (with an audio clip). We interviewed David Gozal about his study on the link between childhood obesity and lack of sleep, and took a look at NCAA regulations mandating sickle cell testing for athletes.

February

Harold Pollack gave a lecture on why violent crime in urban, minority communities should be considered a public health epidemic. Siri Atma Greeley studied the actual medical benefit of widespread genetic testing. Stacy Lindau wanted to know why so few women get help for sexual problems after surviving cancer. We talked to Bana Jabri about the causes of celiac disease, and Sliman Bensmaïa showed us how the brain processes the basic elements of touch very much like it handles visual information.

March

Sola Olopade educated women in Nigeria about using clean-burning stoves to prevent indoor pollution. Stefano Allesina and Jonathan Levine looked at how rock-paper-scissors helps explain evolution. Joshua Miller went to Yellowstone Park to see what stories the ghostly bones of animals can tell, and Scott Eggener questioned the wisdom of indiscriminate prostate cancer screening.

Photo by Gerald Waddell

Andrea King studied the wide range of responses to drinking alcohol, and why it can be fun for some people and a bummer for others. Cheryl Reed took a ride in a helicopter with our UCAN nurses. Kamal Sharma looked at the genes that control animals’ gait, and Ningqi Hou studied how urban environments can dictate how much exercise people get.

May

Daniel McGehee looked at the long-term effects of nicotine on the brain. Habibul Ahsan went to Bangladesh to study the health impacts of accidental exposure to arsenic in drinking water. The brain’s overlooked supporting cells got their due at a conference on neuroscience, and we remembered a landmark discovery about a once popular drug taken during pregnancy that we now know can cause cancer.

June

As we headed into summer, Diana Lauderdale used Google to track MRSA. We learned about an extraordinary transplant where a man received a new heart, liver AND kidney. Daniel Geynisman gave us the rundown on whether or not cell phones are killing us (they’re not, as long as you don’t use them in the car), and some UChicago undergrads studied what happens to gorillas on the birth control pill.

July

We spoke to Donald Jensen and Andrew Aronsohn about the new outlook for patients with hepatitis C. Igor Schneider made a time machine to find the genetic switch for limb development. Farr Curlin led a study about the benefits of addressing spiritual needs alongside medical care, and Adam Cifu looked at the phenomenon of scientific study reversals.

August

Stefano Allesina dug into the long, shady history of nepotism in academia in Italy. John Schneider talked about his work addressing sexual health and stigma in India. Michael Becker discovered a new treatment for the Royal Disease, and we had the rare chance to name check a Spiderman villain in a post.

September

Martha McClintock and Suzanne Conzen studied the connection between social isolation, stress and breast cancer. Gallego Romero traveled to India to search for the origins of lactose intolerance. Stephanie Dulawa developed a mouse model for OCD, and Paul Vezina looked at a different kind of obsession, compulsive gambling.

October

Arshiya Baig started a pilot project to help people learn about life with diabetes through pictures. Manyuan Long found that some of the youngest genes are in the brain. Jens Ludwig and Stacy Lindau published a landmark study about the connection between neighborhood poverty and health, and Issam Awad studied a rare brain disease that soon could be treated with a drug instead of surgery.

November

Cathy Pfister and Tim Wootton figured out how to use seashells to track climate change over the years. Lianne Kurina found a link between loneliness and sleep quality. Shantanu Nundy, Monica Peek and Marshall Chin developed a program to send text message reminders to people with diabetes, and Pan Chen looked at the links between childhood abuse and aggressive behavior in adults.

December

Inbal Ben-Ami Bartal, Jean Decety and Peggy Mason discovered that rats can show empathy for their fellow rats in distress. Maciej Lesniak performed a scary but amazing brain surgery on a patient who was awake. Cathryn Nagler searched for the source of food allergies within our bodies, while Stafano Guandalini uncovered the challenges in educating doctors about one of those allergies, celiac disease.

Whew. Hope you were able to click through at least a few of those. We look forward to another great year of research in 2012. We’re taking a break next week, but we’ll be back on January 5. Happy holidays!

If you are an avid reader of food packaging materials or a parent of an elementary school student, you might get the feeling that food allergies are on the rise. Statistics back up this notion, with the CDC reporting an 18 percent increase [pdf] in child food allergies between 1997 or 2007. That puts current estimates of food allergy prevalence at 4 percent for children and 2 percent for adults, with allergies to peanuts (3.3 million Americans) and shellfish (6.9 million) leading the way.

The factors driving this surge remain a scientific mystery, and answers are even more scarce when it comes to treating or preventing dangerous allergic reactions. Currently, the only way to prevent anaphylaxis caused by a food allergy is avoidance, a strategy that can be very cumbersome for parents raising small children who cannot be exposed to basic food groups. Dave and Denise Bunning faced this challenge with their two children, both of whom were allergic to milk and eggs, leading to “several emergency room visits before the age of 5,” Dave Bunning said. Those experiences inspired the family’s philanthropy for research into the science of food allergies, which included this year’s founding of the Bunning Food Allergy Professorship at the University of Chicago Medical Center.

At the official naming ceremony for the new position, the inaugural Bunning Food Allergy Professor Cathryn Nagler presented her latest research to a large crowd including the Bunning family themselves. Nagler’s intriguing theory about food allergies looks within, at the bacterial universes that exist inside the human body. In parallel with other laboratories on campus looking at the impact of the human “microbiome” upon diseases such as inflammatory bowel disease and diabetes, Nagler is focused on the trillions of bacterial tenants that occupy each of our bodies.

“It’s becoming clear that we are outnumbered,” Nagler said. “There are 10 trillion human cells encoding 20,000 genes [in an individual], but 100 trillion bacterial cells encoding an estimated 2 to 20 million genes. So there are as many E. coli in each of our digestive tracts as there are people on Earth…and that’s not even one of the more popular species.”

All those bacteria, sometimes called the “commensal microbiota” to distinguish them from disease-causing pathogens, could play the environment role in the genes + environment recipe for food allergies. Many of the trappings of modern life, including high-fat diets, antibiotic treatments, and the use of baby formula instead of breastfeeding, can affect the census of our bacterial inhabitants. In food allergies, where the immune system mistakenly treats innocuous dietary proteins as harmful invaders, these microbiota changes might tip the balance towards over-sensitivity to components of peanuts or shrimp.

“An increase in disease prevalence in 10 to 15 years’ time can’t be explained by genetics, so there’s got to be other factors that are driving this increase in disease prevalence,” Nagler said. “All of these environmental variables lead to alterations of the commensal microbiota, which in genetically susceptible individuals could drive allergic responses to food and other antigens.”

To study this model, Nagler’s laboratory gave a long-term treatment of antibiotics to lab mice, finding that this prolonged exposure did indeed trigger an allergic response to peanuts. Using genetic identification methods, her group compared the gut microbiomes of mice treated with antibiotics versus mice who did not receive the drugs, finding several differences in the bacterial populations colonizing their digestive system. One bacterial family, called Clostridia, were reduced in the mice treated with antibiotics, while another was increased — suggesting that reducing or decreasing different species of bacteria might affect the chances of developing food allergy.

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By John Easton

Even in the court of ethics and medical professionalism, there’s nothing wrong with the occasional honor or award. On day two of the conference, the Maclean Center awarded its first Prize in Clinical Ethics and Health Outcomes - at $50,000, the largest such prize in the ethics field - to John Wennberg, the Peggy Y. Thomson Professor for Evaluative Clinical Sciences at Dartmouth Medical School and founding editor of The Dartmouth Atlas of Health Care.

In 2007, the journal Health Affairs named Wennberg as “the most influential health policy researcher of the past 25 years.” Fitzhugh Mullan, former director of the Bureau of Health Professions in the U.S. Department of Health and Human Services, described Wennberg as “both the Christopher Columbus and the Johnny Appleseed of clinical variation,” meaning he not only discovered the field but also brought it to the attention of the medical and health policy communities.

“While John Wennberg is regarded as a health services researcher,” said Mark Siegler, MD, director of the MacLean Center, “his fundamental work on patient preferences and shared decision making highlight his contributions to the field of clinical medical ethics.”

The Dartmouth Atlas examines the patterns of medical resource intensity and utilization in the United States, with special emphasis on end-of-life care, inequities in the Medicare reimbursement system and the under-use of preventive care.

From the start, it has brought surprises, according to Kenneth Polonsky, dean of the Division of the Biological Sciences and the Pritzker School of Medicine at the University of Chicago, who introduced Wennberg. The report comprehensively documented the “striking differences” in the amount of health care provided in different regions, adding the provocative observation that the amount or cost of care delivered did not correlate with good outcomes.

Joking that “when you get paid so much to give a lecture, you get a little nervous,” Wennberg spoke about the early days of the Atlas and how their studies of practice variation in the mid-1970s “challenged the notion that science was driving utilization.” Instead, decisions about surgical treatment for benign prostate hyperplasia revealed what the researchers called “surgical signatures,” patterns of practice based on the beliefs of individual surgeons.

When Wennberg’s team developed short, balanced videos to show to patients, explaining the risks and benefits of surgical treatment and showing taped interviews with two physicians who had made different decisions, patients were much less likely to choose surgery. “This was the first evidence,” he said, “that engagement of patients could lead to the right utilization rate.”

However, only about 25 percent of medical care turns out to be so “preference-sensitive,” forming what Wennberg calls “little islands of rationality.” Studies of end-of-life care found a far more limited role for shared decision making between patients and their caregivers. Instead, demand for resources appears to be driven by supply. Empty hospital beds and unused capacity strongly correlate with increased medical care late in life. For example, more than twice as many patients were admitted to an intensive care unit in the last six months of life at UCLA compared to Dartmouth.

Wennberg described the four goals of the Atlas’s end-of-life team for the next five years: to better inform patient choices, improve the science behind these decisions, promote organized care and constrain undisciplined capacity spending. At this point, he said, “we don’t need more research, we need more action.”

Another session at the conference focused on a very different book, not an atlas but a historical novel, based on true events and real people. Open Wound: The Tragic Obsession of Dr. William Beaumont, by former ethics fellow Jason Karlawish, a professor of medicine and medical ethics at the University of Pennsylvania, examines the professional and ethical issues raised by William Beaumont, a 19th-century surgeon who cared for - and experimented on - a patient with a shotgun-blast-induced hole in his stomach. Beaumont saved the patient’s life, but then used this wound, which never quite healed, as a window to decipher the mysteries of digestion.

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Loneliness has had a tough run of late, with a growing body of research blaming it for everything from high blood pressure to heart disease to depression and cognitive decline. The research group of John Cacioppo, director of the Center for Cognitive and Social Neuroscience at the University of Chicago, has been among the leaders in leveling these medical charges against loneliness. But one missing piece of the puzzle remains - what biological mechanism connects a person’s feelings of inadequate social contact with the negative health outcomes? A new collaboration with epidemiologists and geneticists at the Medical Center suggest that the missing link might be in the bedroom.

For decades, professor of human genetics Carole Ober has studied a unique society called the Hutterites [pdf]. A religious group that originated in the 16th century, the Hutterites have formed several communal farms in the United States where some 150 people live and work together. The stability and isolation of the Hutterites make them a perfect population for studying the interplay between genes, environment, and disease - the mission of Ober’s research. Those qualities also made them the perfect group of people for a team lead by Lianne Kurina, assistant professor of epidemiology in the University of Chicago Department of Health Studies, to test the link between loneliness and sleep quality.

The new study, which appears in the journal Sleep, is not the first to examine this connection. A 2002 study led by Cacioppo used the most accessible pool of subjects on a college campus - college students - and found that those who scored higher on a psychological loneliness test displayed reduced sleep “efficiency” with no change in sleep duration. In other words, the loneliest subjects slept just as long as their socially satisfied peers, but suffered more “microawakenings” and lower sleep quality.

Because college students reflect only a narrow band of society, it was important to replicate the result in an entirely different population. Enter the Hutterites, who were also tested using a loneliness scale and asked to wear wristband sleep monitors to track their activity during sleep. Because of their communal lifestyle, even the loneliest Hutterites were less lonely than the general population. But the same correlation was detected between loneliness and sleep quality - for each point increase on the loneliness scale used to test the subjects’ social feelings, the researchers observed an 8 percent increase in sleep fragmentation. Furthermore, the lonelier Hutterites did not themselves report poor sleep or daytime sleepiness, indicating that the effects are mostly subconscious.

“Loneliness has been associated with adverse effects on health,” Kurina said in a press release. “We wanted to explore one potential pathway for this, the theory that sleep - a key behavior to staying healthy - could be compromised by feelings of loneliness. What we found was that loneliness does not appear to change the total amount of sleep in individuals, but awakens them more times during the night.”

The evidence is still not strong enough to conclusively place sleep deficits as the intermediary between loneliness and poor health. As the paper admits, the opposite relationship could be true: sleep fragmentation could increase feelings of social disconnection. But a flood of recent evidence, much of it from the University of Chicago Sleep, Metabolism, and Health Center, suggests that the third of each day we spend sleeping can dramatically affect several different aspects of our health, including diabetes, obesity, dieting success, and testosterone levels. Certainly, the newly replicated connection between a lonely heart and restless nights offers an intriguing theory for future study.

But why would feelings of social inadequacy disrupt a person’s time in bed?

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Biology used to be the scientific discipline where data was at a premium, a rare resource painstakingly collected in the field or the laboratory. But today’s biologists are confronted with a flood of data, a fire-hose torrent of genetic and clinical information that only builds with the spread of fast sequencing and electronic medical records. But as these databases fill terabyte after terabyte of computer storage, the successful transformation of that data into practical information about human biology and disease has lagged behind. Genome-wide association studies (GWAS) have  explained only a small percentage of disease heritability, clinical records remain largely unstudied on a large scale, and the complications created by environmental influences and multi-gene disorders have frustrated scientists.

Into this impasse comes a new multi-institutional project based at the University of Chicago: the Silvio O. Conte Center, funded by a nearly $14 million combination of grants from the National Institute of Mental Health and the Chicago Biomedical Consortium. Led by Andrey Rzhetsky, professor of medicine and human genetics at the Medical Center, the collaboration of 15 scientists from 7 institutions will apply the power of advanced computation and data-mining to the growing tide of data collected about neuropsychiatric disorders. The trick will be to not just focus on one database, be it genetics or environmental factors or clinical outcomes, but all of them at once, creating a higher-resolution image of what goes awry in the brain to cause mental disease.

“A great deal of data already exists, yet nobody is already looking at it the way we plan to do and we have very smart people on this team,” said Rzhetsky, who is also a senior fellow of the Computation Institute at the University of Chicago and Institute for Genomics and Systems Biology. “When you have multiple communities that partially study the same subject you can get a kind of three-dimensional picture of a phenomenon.”

Rzhetsky has previously demonstrated the promise of data-mining - the discovery of patterns and information in large pools of data - using clinical records and scientific literature. In a 2007 study, his team examined 1.5 million patient records and found significant overlap between mental disorders such as schizophrenia, bipolar disorder, and autism, suggesting a similar overlap of the genetic factors that cause these conditions. Two years later, Rzhetsky and colleagues applied text-mining computation to the scientific literature database PubMed, creating a network of genes and biological interactions associated with cerebellar conditions such as ataxia and degeneration.

Beyond demonstrating the potential of data-mining, those studies also shed light on the hazy borders separating different psychiatric disorders. While the overlaps could complicate psychiatric diagnosis in the clinic, they might also make the disorders susceptible to the multi-faceted approach proposed by the Conte Center.

“Most studies are done one disorder at a time, and that’s like studying the trunk or the hoof or the tail of an elephant; you might miss the big picture,” said Benjamin Lahey, Irving B. Harris Professor of epidemiology at the University of Chicago and a co-investigator at the Conte Center. “This project will enable us to look at things in a way that has never been done before, at a scale that dwarfs anything that’s ever been done.”

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Last November, a barrier was broken in the prolific Bollywood film industry of India. A film called Dunno Y featured the first on-screen male-male kiss - a provocative scene in a country that only the year before repealed a law making homosexuality illegal. Many tagged the film as India’s version of Brokeback Mountain, a controversial and progressive step in depicting male-male romance in popular culture that reflected a growing social acceptance of homosexuality. But the full significance of those cultural changes in the South Asian country have yet to be studied, and will require perspectives from law, anthropology, medicine, and more.

Just such a discussion will take place this Saturday morning at the University of Chicago and on the internet in the roundtable event, “Sexual Identity, Health and Stigma in India: Traditional Statuses and Western Influences.” Organized by John Schneider, assistant professor of medicine and epidemiology at the University of Chicago Medical Center and director of Global Health Programs, the discussion will be available worldwide on a webcast broadcast by the UChicago Facebook page, the Global Health Initiative website, and here on ScienceLife (watch this space).

“What I tried to do is bring together scholars from a number of different disciplines to make this a truly interdisciplinary discussion,” Schneider said. “I want it to be like a Sunday morning news program - but smarter - where a topic area is chosen and everybody fires away with their background about it, leaving room for remote viewer input.”

The central topic of whether sexual identity in India is truly shifting can be addressed from any number of angles. There’s the legal status of homosexuality after the 2009 repeal of Section 377 of the Indian Penal Code by the High Court of Mumbai. Or the sexual and mental health consequences after centuries of stigmatization of men having sex with men, including the spread of HIV and other sexually transmitted diseases. Or the pop culture ripples, such as Dunno Y, that may reflect changing attitudes and sexual roles in Indian culture. All of which are set against the backdrop of a country rapidly modernizing and playing an increasingly powerful role in global economy and society.

“I think that India is going through tremendous social and cultural changes as it emerges from what would be, in old terms, a less-developed economy to now becoming something of an economic powerhouse,” said Niranjan Karnik, assistant professor of psychiatry and behavioral neuroscience and another participant in the event. “This has the potential to really change the dynamics of the society and change the way people see themselves and behaviors.”

The participants in the roundtable are all accomplished researchers and experts on India. The keynote speaker, Lawrence Cohen of the University of California, Berkeley, studies medical anthropology in the country, and has written on homosexuality, aging, and organ transplant markets. Philip Kumar and Sanjay Srivastava are researchers based in India studying sexuality and advising the government on health issues related to men who have sex with men. Schneider himself has an extensive project underway in Indian truck drivers, where he is using cell phones in building a network of men who have sex with men to study their behavior and identify potential peer outreach points.

“One of the issues we are looking at is what changes in sex position roles might be occurring over time in India,” Schneider said. “Is a Western identity rubbing off on India, or is it developing a new identity? My work will help address those questions because of the cell phone network data that triangulates often sensitive self-reported data,” Schneider said.

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Being a parent these days is anxious business, with an onslaught of news reports telling you what might be good or bad for your child’s health and development. In many cases, these claims are based on scientific evidence that is preliminary at best, studied only in small subject pools or retrospectively. To comprehensively confirm a link between, say, breast-feeding and body weight or living near a smokestack and asthma, a large epidemiological study that tracks thousands of children from before birth to adulthood is necessary. But that kind of study is very expensive, thanks to costs associated with recruitment, data collection, and analysis over decades of time.

As such, it’s better to do one enormous study of many factors that potentially influence child health rather than several independent and costly experiments. Enter the $5 billion National Children’s Study, a federally-funded project that hopes to track over 100,000 American children from their mother’s womb to age 21 in order to test possible influences - genetic and environmental, positive and negative - to their health. Already 11 years in the making, the study is just completing its warm-up phase, hoping to start the main event in April 2012. But as Daniel Johnson and Angela DeBello presented at the University of Chicago Medical Center Pediatric Grand Rounds earlier this month, the study is already teaching researchers valuable lessons.

“We have a very ambitious agenda,” said Johnson, an associate professor of pediatrics at the Medical Center involved in the Chicago branch of the study. “We’re kind of learning how to do this as we’re going along.”

The Children’s Health Study was authorized as part of the Children’s Health Act of 2000, alongside improvements to child mental health care, anti-violence programs, and day care provider training. While many of the other initiatives have long been implemented, the CHS has taken more time to reach the launchpad due to the mind-boggling logistics involved. In order to break down the roughly 4 million U.S. births each year into a manageable study cohort, the project will collect medical and survey data on growing kids from 105 different counties reflecting almost every region of the country.

It’s a beautiful plan on paper, but executing the recruitment and retention of 100,000 children around the country is immensely difficult. Debello, the vice president and associate director of public health research at the National Opinion Research Center (one of the organizations charged with administering the CHS), said that pilot studies have revealed just how difficult it is to even find pregnant mothers eligible for the study. Researchers have tried surveying homes for women expecting children or trying to have children, working with medical providers who can direct eligible women to the study, and mailed surveys to try and find the right subjects. But the up-to-date numbers presented at grand rounds indicated the low hit rate of this full court press: of 28,000 households originally contacted in Cook County, only 67 women were found to be eligible for the study (and only 49 provided consent to participate).

“It’s pretty overwhelming…the numbers are going to get big very quickly as this study progresses,” DeBello said. “Not surprisingly, it was far more expensive than we expected it to be.”

Hence that large price tag, which Johnson admitted is high, while also suggesting that it could be a bargain in the end. Any costs spent on conducting the study should be weighed against the potential health care costs saved with the information it collects. There’s a lot of room to work with in child health costs, he pointed out - a study in the journal Health Affairs calculated that environmentally-mediated diseases caused by lead exposure, air pollution, and other toxins produced $76 billion in medical costs in 2008 alone. Johnson also pointed out that the results of a similarly large project, the Framingham Heart Study, has prevented an estimated 800,000 deaths despite only being 1/20th the size of the CHS.

“It’s still not clear how successful this study will be,” Johnson said. “But we think that the goals and aspirations are certainly strong reasons to drive us forward.”

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When the media fixates on a medical topic, doctors know that a flurry of patient questions will inevitably follow. So it helps to be prepared with responses to hot-button questions, such as those surrounding the recent resurgence of the potential link between cell phones and brain cancer. Inspired by the World Health Organization moving the radiofrequency magnetic fields produced by cell phones to the classification of “possibly” causing cancer in late May, some newspapers handled the topic with subtle headlines like IS YOUR CELL PHONE KILLING YOU?. Though the fevered media response of some outlets was countered by thoughtful explainers from other sources, many physicians will surely still face questions from patients on the topic. But how does a busy doctor brush up on the extensive literature testing the link between cell phones and cancer?

A: You attend a literature review talk, such as the one given by hematology/oncology fellow Daniel Geynisman at Monday’s installment of the department’s weekly seminar. In half an hour, Geynisman sped through the most important studies examining cell phones and brain cancer, drawing out the important results, criticisms, and implications of the experiments. The primary message was simple - there’s no need to panic, or to go back to using exclusively landlines and pagers. But a true danger does exist with cell phones, Geynisman said, one that’s worth sending a warning to patients - and doctors themselves.

The lingering mystery around cell phones and cancer is caused by an epidemiological quirk, Geynisman explained. Proving the link between a rare exposure and a rare cancer - such as asbestos and mesothelioma - is relatively straightforward. Finding a link between a common exposure and a common cancer is more difficult, but can be done, as it was with smoking and lung cancer. But conclusively proving the connection between a common exposure, such as cell phones, with a rare cancer, such as glioma or acoustic neuroma, is much more difficult. Only about 10,000 new cases of glioma are diagnosed each year in the United States, while more than 300 million cell phones are currently in use in the country. To prove that the use of phones significantly increases brain cancer rates, enormous numbers of subjects would have to be collected and followed.

Those challenges have forced most researchers into a flawed study design, Geynisman said. Retrospective case control studies are commonly used in epidemiology, but are subject to an important confounding factor called recall bias. If you ask 3,000 people with brain tumors and 3,000 controls about their history of cell phone use, those with  cancer are more likely to remember and report unusually high amounts of use. In one study, subjects were found to over-estimate their cell phone use by almost three times, adding a hefty dose of salt to any case control results.

Despite this issue, early case control studies found a relative risk of 1, indicating no increased or decreased risk for brain tumors in users of cell phones. But the question did not go away, fueled by the research of a Swedish group who dialed the data down to find increased risk among very specific groups: people who used cell phones for more than 10 years, or people who started using the phones before the age of 20. The INTERPHONE study, which surveyed over 6,000 people with brain tumors and 7,000 controls from 13 countries, might have settled the dispute but for one result. Published last year, most of the risks calculated for various groups and tumors showed a negative association with cell phone use, suggesting (improbably) that talking on the phone protected against brain cancer. But one association still stuck out - heavy cell phone users showed a 40 percent increase in the risk of glioma. Statistical anomaly, or cause for concern?

The result was apparently enough for the WHO to place cell phone radiation in the same group as other potentially carcinogenic compounds ranging from lead and coffee, and for more studies to be conducted, Geynisman said. After all, ubiquitous cell phone use is a relatively recent development, so more time may need to pass before the health effects can be accurately assessed. A prospective study, called COSMOS, will tackle some of these questions, as it follows a quarter-million subjects for at least 25 years and measures cell phone use as it happens, instead of through memory. But while scientists, physicians, reporters, and the general public wait for those results, they can caution the world about the real dangers of cell phones, which have nothing to do with cancer.

“What’s not shaky is that cell phone users are four times more likely to be distracted drivers and texting poses a risk of 23 times more collisions. 81 percent of Americans use their cell phones while driving, and almost a third of crashes involve cell phones,” Geynisman said. “So you can keep using your cell phone probably, but don’t do it while driving.”

In the 2000s, a new kind of genetic experiment was born: the genome-wide association study, or GWAS. If geneticists could recruit enough people with a particular disease and compare them to an equal number of disease-free controls, they believed GWAS would point the way to common gene variants associated with disease risk and novel biological pathways. One of the strengths of GWAS was that it was hypothesis-free, an unbiased comparison that could reveal surprising risk-associated genes that had not occurred to scientists in the past. More than 1,000 GWAS studies have been conducted to date, on diseases ranging from diabetes to Parkinson’s disease to Crohn’s disease to various types of cancer.

While these studies have identified thousands of gene variants (called single nucleotide polymorphisms, or SNPs) associated with disease risk, they can still only explain a small fraction of the heritability of disease. Some scientists have thus moved on from GWAS to the next wave of genetic studies, including whole-genome sequencing to look for rare variants and gene-environment interaction studies. But some geneticists think the field may be moving too quickly onto the next big thing, and that there remains value in the volumes of GWAS data collected over the last decade. A second generation of GWAS is taking place, where the data from the first round is approached in new ways to find previously hidden gems of information.

In two recent studies, assistant professor of health studies Brandon Pierce applied this Reuse/Recycle/Reduce philosophy to GWAS data on pancreatic cancer risk, a disease where genetic and biological explanations are particularly lacking. For both experiments, Pierce bended the “hypothesis-free” rule of GWAS in order to narrow the field of gene variant candidates and allow for a more selective scan of pre-existing data. By reducing the number of candidates from the ~550,000 of a full GWAS, the statistical threshold for confirming a SNP association with risk can be set lower. If the original GWAS experiments were the equivalent of looking for a needle in a haystack, the new techniques are a much less daunting task, he said.

“You conduct fewer tests, so the haystack is smaller,” Pierce said. “In all of the tests you are conducting, you know the SNPs are biologically meaningful, whereas in a typical GWAS, a large percentage of the SNPs may have very little to do with human biology.”

In the first study, published in March in Cancer Causes & Control, Pierce adapted a connection discovered by epidemiology studies to his genetic scan. Patients with type 2 diabetes were measured to have elevated risk for pancreatic cancer - a logical relationship given that diabetes is primarily a disease of the pancreas. Pierce took 37  SNPs associated with type 2 diabetes and tested them in the GWAS data collected by a previous study of pancreatic cancer. None of the SNPs tested showed a strong association with pancreatic cancer, though two new gene variants produced suggestive evidence of an association. The results suggested that the biological link between type 2 diabetes and pancreatic cancer may not be as strong as the epidemiology data indicated.

“We didn’t find any major associations that popped out at us from the diabetes study, so the conclusion was that these established genes for type 2 diabetes don’t seem to have a big effect on pancreatic cancer risk,” Pierce said.

But a second study, published in Cancer Research, would lead Pierce almost full circle. This time around, he ran the pancreatic cancer GWAS data through what he dubbed a “pleiotropy scan,” testing only SNPs previously demonstrated to have a biological effect in humans. For many of the more than half-million SNPs typically tested in a GWAS, scientists have yet to discover a linkage to any disease or biological effect, suggesting that these markers may sit without effect in the long gaps between protein-encoding genes in human DNA. Like the first study, limiting his GWAS tests to only these SNPs (1,087 in this case) allowed Pierce to pick up more subtle associations than in a full-blown GWAS.

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A Magic 8-Ball for Cardiac Arrest

Cardiac arrest is one of the most common ways that people die, and hospitals need to be constantly vigilant about the threat of heart stoppage in their patients. So physicians have long sought to develop a way of predicting who is most at risk for cardiac arrest when checked into the hospital, such that extra care and surveillance can be taken. At the 2011 international meeting of the American Thoracic Society, held this past week in Denver, two Medical Center fellows presented research refining these early warning systems to make them a more effective hospital tool.

In the first study, pulmonary and critical care fellow Gordon E. Carr connected cardiac arrest with another frequent sight on the hospital ward: pneumonia. Carr’s study found that patients admitted with pneumonia are at elevated risk of cardiac arrest over the next three days after admission, and that almost 40 percent of these cardiac arrests occurred while the patient was outside of the intensive care unit. “We found a compelling signal that some patients with pneumonia may develop cardiac arrest outside of the ICU, without apparent shock or respiratory failure,” Carr said in a press release. “If this is true, then we need to improve how we assess risk in pneumonia.”

Adding extra caution about cardiac arrest to the care of patients with pneumonia is a specific way to improve surveillance. But to apply to more patients, a broader scale is needed, one that can be easily assembled from the vital signs that are already routinely measured in the wards. One such scale, called the Modified Early Warning Score or MEWS was tested by pulmonary and critical care fellow Matthew Churpek as a predictor of cardiac arrest, who found it to be better at predicting a cardiac arrest in the next 48 hours than any individual vital sign. But MEWS was designed for general risk of death, not specifically for cardiac arrest, and Churpek suggested a more specialized risk score could be calculated for use by hospitals. The benefits of such a measure, he said in a press release, would be immense.

“Rapid response teams are a complex and resource-intensive intervention, so providing evidence-based criteria for their activation is crucial,” Churpek said. “Our patients will do better if we can detect who is at high risk early enough to intervene and prevent a cardiac arrest.”

Doctors Against Ronald McDonald

Childhood obesity is a growing problem in the United States, and doctors point the finger of blame directly at increased consumption of junk food and fast food. Chains such as McDonalds have made noise about making their food healthier, especially for children, by posting calorie counts on menus and offering snacks such as apples and carrots instead of fries. But according to an open letter signed by over 500 health care professionals and placed in newspapers around the country this week, they have not done enough.

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Today, nearly everyone is aware of the dangerous health effects of smoking cigarettes. Even fewer people would deny the harmful effects of drinking water contaminated with arsenic. But when these two toxic influences are mixed together, is the sum of their damage more than the individual effect of each? To put it another way: for a person in an area with low, “safe” amounts of arsenic in the groundwater smokes, is their risk of disease increased as though they were drinking unsafely contaminated water?

To study this question, University of Chicago epidemiologist Habibul Ahsan returned to his project studying the consequences of accidental arsenic exposure in the people of Bangladesh. Ahsan’s Health Effects of Arsenic Longitudinal Study (HEALS) has tracked thousands of Bangladeshi citizens who unknowingly consumed well water with high levels of arsenic after health organizations installed wells to reduce water-borne infectious disease. That study, which has expanded to 20,000 subjects, discovered a 70 percent higher risk of death from chronic disease in those drinking water with the highest levels of arsenic. Even people exposed to moderate levels of arsenic, amounts that can be found naturally in some regions of the United States, were at a 20 to 30 percent higher risk of dying from chronic disease.

Ahsan and his team from UChicago, Columbia University, New York University, and Bangladesh, looked at whether the combination of arsenic exposure and smoking made the odds even scarier on one particular mortality endpoint: cardiovascular disease. While arsenic is traditionally thought of as causing different types of cancer and skin lesions, chronic exposure can also produce various heart and circulatory problems such as hypertension and atherosclerosis. Previous studies of these cardiovascular effects have been small, retrospective, and focused on extremely high exposures in Taiwan and Chile. With the Bangladesh study, Ahsan and colleagues could look at a broader spectrum of exposure, and follow subjects carefully over time to isolate the effect of arsenic from other factors.

For the study, published last week in the British Medical Journal, the researchers tracked nearly 12,000 Bangladeshis, taking urine samples to measure arsenic exposure and registering the cause of death in those who died over the time they were tracked (an average of 6.6 years). Overall, 460 subjects died, with nearly half of those (198 people) dying from some form of cardiovascular disease. Associating those deaths with arsenic exposure confirmed the Taiwan and Chile studies on people exposed to high concentrations (as high as 80 times the safe limit of 10 parts per million) of the toxin. But a worrisome trend also emerged for more moderate exposures, with a 50 percent increase in cardiovascular mortality risk observed at levels as low as 2.5 times the safe limit.

“We were able to show that, even at lower doses than previously reported, there seems to be a deleterious effect of arsenic regarding cardiovascular disease mortality, particularly from ischemic and other heart diseases,” Ahsan said.

For those subjects who were smokers - even those who had quit - a deadly synergy emerged. For a current smoker exposed to the high levels of arsenic, the increased risk of dying from cardiovascular disease jumped from 50 percent to 328 percent. Former smokers saw a lower bump in risk, but if exposed to moderate levels of arsenic, they shared the same risk as those exposed to high levels that had never smoked. Ahsan said that the result emphasized the importance of targeting multiple risk factors in improving public health around the world.

“This tells us that there are some individuals who are dying from cardiovascular disease solely because of the presence of both factors, not because of the presence of one or the other,” Ahsan said. “It’s one more reason to pay attention to arsenic exposure, but yet another reason that will underscore the importance of smoking cessation.”

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