Measuring depression with wearables

Depression and emotional disorders can occur at any time of year — and do for millions of Americans. But feeling sad, lonely, anxious and depressed may seem particularly isolating during this holiday season, which is supposed to be a time of joy and celebration.

A team of Stanford researchers believes that one way to work towards ameliorating this suffering is to develop a better way to quantitatively measure stress, anxiety and depression.

“One of the biggest barriers for psychiatry in the field that I work in is that we don’t have objective tests. So the way that we assess mental health conditions and risks for them is by interview and asking you how do you feel,” said Leanne Williams, MD, a professor in psychiatry and behavioral sciences at Stanford, when she spoke at a Stanford Reunion Homecoming alumni celebration.

She added, “Imagine if you were diagnosing and treating diabetes without tests, without sensors. It’s really impossible to imagine, yet that is what we’re doing for mental health, right now.”

Instead, Stanford researchers want to collect and analyze data from wearable devices to quantitatively characterize mental states. The multidisciplinary team includes scientists from the departments of psychiatry, chemical engineering, bioengineering, computer science and global health.

Their first step was to use functional magnetic resonance imaging to map the brain activity of healthy controls compared to people with major depressive disorder who were imaged before and after they were treated with antidepressants.

The researchers identified six “biotypes” of depression, representing different ways brain circuitry can be disrupted to cause specific symptoms. They classified the biotypes as rumination, anxious avoidance, threat dysregulation, anhedonia, cognitive dyscontrol and inattention.

“For example, threat dysregulation is when the brain stays in alarm mode after acute stress and you feel heart racing, palpitations, sometimes panic attacks,” presented Williams, “and that’s the brain not switching off from that mode,” Williams said.

The team, which includes chemical engineer Zhenan Bao, PhD, then identified links between these different brain biotypes and various physiological differences, including changes in heart rate, skin conductance, electrolyte levels and hormone production. In particular, they found correlations between the biotypes and production of cortisol, a hormone strongly related to stress level.

Now, they are developing a wearable device — called MENTAID — that measures the physiological parameters continuously. Their current prototype can already measure cortisol levels in sweat in agreement with standard laboratory measurements. This was an incredibly challenging task due to the extremely low concentration and tiny molecular size of cortisol.

Going forward, they plan to validate their wearable device with clinical trials, including studies to assess its design and user interface. Ultimately, the researchers hope MENTAID will help prevent and treat mental illness — for example, by better predicting and evaluating patient response to specific anti-depressants.

Photo by Sora Sagano

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

X-rays shed light on how anti-asthmatic drugs work

A new study uncovers how a critical protein binds to drugs used to treat asthma and other inflammatory diseases.

By studying the crystal structure of an important protein when it was bound to two drugs widely prescribed to treat asthma, an international team of scientists has discovered unique binding and signaling mechanisms that could lead to the development of more effective treatments for asthma and other inflammatory diseases.

The protein, called cysteinyl leukotriene receptor type 1 (CysLT1R), controls the dilation and inflammation of bronchial tubes in the lungs. It is therefore one of the primary targets for anti-asthma drugs, including the two drugs studied: zafirlukast, which acts on inflammatory cells in the lungs, and pranlukast, which reduces bronchospasms due to allergic reactions.

Using the Linac Coherent Light Source (LCLS) X-ray free-electron laser at the Department of Energy’s SLAC National Accelerator Laboratory, the team bombarded tiny crystals of CysLT1R-zafirlukast with X-ray pulses and measured its structure. They also used X-rays from the European Synchrotron Radiation Facility in Grenoble, France to collect data about CysLT1R-pran crystals. They published their findings in October in Science Advances.

The researchers gained a new understanding of how CysLT1R interacts with these anti-asthma drugs, observing surprising structural features and a new activation mechanism. For example, the study revealed major differences between how the two drugs attached to the binding site of the protein. In comparison to pranlukast, the zafirlukast molecule jammed open the entrance gate of CysLT1R’s binding site into a much wider configuration. This improved understanding of the protein suggests a new rationale for designing more effective anti-asthma drugs.

The study was performed by a collaboration of researchers at SLAC; Moscow Institute of Physics and Technology, Russia; University de Sherbrooke, Canada; University of Southern California; Research Center Juelich, Germany; Universite Grenoble Alpes-CEA-CNRS, France; Czech Academy of Sciences, Czech Republic; and Arizona State University.

Citation: Aleksandra Luginina et al., Science Advances, 09 October 2019 (10.1126/sciadv.aax2518).

For questions or comments, contact the SLAC Office of Communications at communications@slac.stanford.edu.

Image caption: Using X-rays, researchers uncovered details about two drugs widely prescribed to treat asthma: pranlukast (shown up top) and zafirlukast (shown beneath). Their results revealed major differences between how the two drugs attached to the binding site of the receptor protein. In comparison to pranlukast, the zafirlukast molecule jammed open the entrance gate of protein’s binding site into a much wider configuration. (10.1126/sciadv.aax2518)

This is a reposting of my SLAC news story, courtesy of SLAC Linear Accelerator Laboratory.

Testing infants’ blood may predict psychological health, study finds

Many of us know that a lipid panel — a simple blood test that measures the levels of cholesterol and fats in the blood — can help predict the risk of heart disease in adults.

What may be more surprising is a Stanford study has now shown that the levels of cholesterol and fat in an infant’s blood can predict that child’s social and emotional development, as recently reported in Psychological Science.

The researchers analyzed data compiled by the Born in Bradford project, which followed children born in the United Kingdom city of Bradford between March 2007 and December 2010.

The Stanford team examined the levels of high-density lipoproteins (HDL) known as “good cholesterol,” very-low-density lipoproteins (VLDL) known as “bad cholesterol” and triglycerides in the umbilical cord blood of 1,369 newborns. Unlike the placenta, all the cells in cord blood are from the fetus.

They then correlated the blood results with the children’s psychological status — including their self-awareness, emotional regulation and interpersonal relationships — as measured five years later by their teachers using standard tests.

The study showed children born with higher levels of HDL, lower levels of VLDL and lower levels of triglycerides were more likely to receive higher teacher ratings than their peers with lower “good cholesterol.”

“It is surprising that from early in life, these easily accessible and commonly examined markers of blood lipid levels have this predictive correlation for future psychological outcomes,” said Erika Manczak, PhD, in a recent Stanford news release. “What our study showed is really an optimistic finding because lipids are relatively easy to manipulate and influence.” Manczak participated in the research as a postdoctoral fellow in psychology at Stanford and is now an assistant professor of psychology at Denver University.

The study, so far, has demonstrated only correlations, not causations. But the findings were consistent across different ethnic and socioeconomic backgrounds and both sexes, where the study participants were 38% white British, 51% Pakistani British, 11% of other ethnicity and 52% male. The associations also held regardless of the mother’s psychological or physical health during pregnancy or the children’s physical health, body mass or neurodevelopmental status.

“The fact that the only solid predictor for the Born in Bradford children’s psychosocial competency assessment scores was their fetal lipid levels really argues in favor of a connection between the two,” Manczak said in the release. “Now we need to find out what exactly this connection may be.”

In the paper, the authors suggest some potential explanations, noting that lipids are involved in many biological processes important to psychological health, such as brain development and inflammation. If future work confirms their findings, they hope lipid screening can help identify and guide treatment for children who are prone to mental illnesses.

Photo by ThorstenF

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Publish or perish: The cost of reformatting academic papers

You’ve probably heard the expression “publish or perish,” which describes the pressure to publish research in order to succeed in an academic career.

You’d think that conducting the research needed to write a paper would be the hard part — and it is. But publishing isn’t easy either, a new Stanford-led study in PLOS One emphasizes. Even top researchers often have to submit papers to multiple journals before getting one to accept it. This process is very time consuming and frankly a bit painful for most authors.

The new study quantifies the pain and cost of a key part of this resubmission process — reformatting the manuscript to another journal’s guidelines.

“All researchers have wasted an inordinate amount of time reformatting papers to another journal’s specific requirements for things like word count, font and figure limits, which is entirely separate from improving the scientific content,” said Sidhartha Sinha, MD, a gastroenterologist and researcher at Stanford. “As medical researchers, we should be spending this time on actual research and patient care, not on adhering to seemingly arbitrary and highly variable formatting requirements.”

So just how detailed are these formatting guidelines? Sinha shared one of his favorite absurd examples taken from a top medical journal: “Type decimal points midline (ie, 23·4, not 23.4). To create a midline decimal on a PC: hold down ALT key and type 0183 on the number pad, or on a Mac: ALT shift 9.”  

He suggests that these rules shouldn’t matter during the initial submission and review process, particularly given that the rejection rate for biomedical journals is 62% on average and over 90% at top tier journals.

Sinha and his colleagues were inspired to study this problem after years of feeling frustrated with the current inefficient process. Although everyone complains about it, very little actual research has been done on the topic, he said.

The team of physicians and editors randomly selected 96 journals focused on basic and clinical biomedical research. They then randomly selected three recently published, original research articles from each journal and sent their survey to the first or corresponding author. A total of 203 authors filled out the survey.

“We had a very high response rate of 72%, which shows that we struck a chord with researchers because it is such a huge problem,” said Sinha. “In fact, only 12% of authors indicated satisfaction with the current resubmission process.”

The survey asked about the time spent by the participating authors and their entire research team to reformat resubmissions for their recent paper. Participants also gave input on the overall reformatting process and how it could be improved.

The study found that most of the 203 authors spent 1 to 3 days or more on reformatting alone, which delayed resubmissions by over two weeks in most instances and up to three months for 20% of the manuscripts.

“It’s not that they are spending three months on reformatting, but they get sidetracked with grant deadlines or other research pursuits,” explained Sinha. “In fact, I currently have one manuscript that is indefinitely on the back burner because I’ve already submitted it a few times and have other research priorities .”

Based on their survey results, the authors estimated that the total time spent reformatting the 2.3 million scientific articles published annually translates into a global cost of over $1 billion. And Sinha said the actual cost is likely much higher — since they assumed, for example, a first-year postdoc salary of $48,000 for all authors even though senior authors make significantly more — and much of this cost is funded by taxpayers’ dollars.

In the paper, the authors make some recommendations — including adopting a universal format-free initial submission policy. However, they primarily hope their study will start a discussion about how to improve the existing broken process, Sinha said.

“There are trends towards minimizing formatting requirements, but there is still much room for improvement,” said Sinha. “I’d like editors from each field to get together and agree on generalized formatting guidelines. For example, maybe brief reports are 3,000 words and original research articles are 6,000 words. And it might be different for radiology and cell biology journals. But we can find a better way to disseminate research faster and more cost-effectively.”

So, like me, are you wondering how much time his team spent on reformatting this paper on publication inefficiencies?  “We kept track and we spent just over 25 hours on reformatting before it was accepted. We hope this paper helps change this in the future,” Sinha said.

Photo by Nic McPhee

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

A twisty career path to improve care for smokers

When Jason Melehani, MD, PhD, grew up in a small town in the Sierra Nevada foothills, he didn’t know any scientists or doctors.

That all changed when he went to college at the University of California, Los Angeles and discovered the world of research. Now, Melehani is a resident in internal medicine at Stanford and his career path, twisty though it may seem, is headed to a future of helping people who have struggled with tobacco use.

At UCLA as a freshman, he joined a lab and began investigating an unusual parasite called Trypanosoma brucei that is transmitted via the bite of a tsetse fly to humans and cattle, causing an often fatal sleeping sickness in Saharan Africa.

“African sleeping sickness exclusively affects very impoverished regions of the world, so there wasn’t much interest from the pharmaceutical industry to develop medicines for this disease,” said Melehani. “A new therapy was recently approved, but it was spearheaded by a nonprofit initiative.”

This research experience inspired his career plan — with the ultimate goal of developing therapies for diseases affecting socioeconomically disadvantaged populations.

First, Melehani headed to the University of North Carolina, Chapel Hill, to earn both a medical degree and doctorate in pharmacology. This program included two years of preclinical medical courses, four years of research and two years of clinical training.  

After completing the MD-PhD program, Melehani took an unconventional approach.  

“Developing new treatments for patients is incredibly challenging especially from an academic lab. You can get things started, but there is a whole world of skills and people required to take things all the way to the clinic,” said Melehani. “I felt like I was experiencing only a thin sliver of the entire process in a research lab.”

To broaden his exposure, he next worked as a fellow at a venture capital firm in North Carolina focusing on healthcare and biotechnology.

“In seven months, I evaluated 500 companies and helped pick the most promising ones, which each received an investment of between half a million to eight million dollars,” said Melehani. “I worked with leaders of major healthcare organizations who valued my opinion despite my junior position. I learned a lot about how new drugs are developed and the role venture capital plays.”

The contacts and insights he gained through this venture capital training and a separate internship in the pharmaceutical industry will likely come in handy in the future when he is running his own academic research lab. “My hope is that this training will help me better select and position future discoveries so I can move them out of my lab to startup companies and ultimately to patients,” he said.

Even at Stanford, Melehani is making his own path. Melehani has applied to do fellowship training next year in both rheumatology and pulmonary medicine, which no one has done before in recent memory.

Melehani plans to research how smoking tobacco affects the immune system and leads to severe health consequences, such as chronic obstructive pulmonary disease, rheumatoid arthritis or heart disease.

“Smoking has disastrous immediate and long term effects on nearly every system in the body,” he said. “And it’s deeply tragic because 90% of people who smoke start before the age of 18 and it’s highly addictive. So even though 70% of people want to quit, the success rates are dismal — around 10%.”

The health impacts of smoking have been on Melehani’s mind for a long time. Many of his friends started smoking in high school. He was exposed to a lot of patients in North Carolina who were smokers. And now at Stanford, he sees many patients who are former smokers and dealing with a wide range of health problems.

Smoking fits his goal of addressing a major socioeconomic health problem— the highest rates of smoking in the United States are in the poorest areas with the lowest education rates. And these are the people who don’t have the resources to face the disastrous health consequences that result, he said.

Melehani hopes to tackle this problem by running his own lab at Stanford, doing fundamental research into how the immune system is affected by cigarette smoke and turning that research into meaningful changes in medical care for his patients.

For now, he is focusing on his patients and getting through his night shifts in the intensive care unit.

Photo of Jason Melehani by Margarita Gallardo

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine

Names matter: Transforming how we label foods

When it comes to food, names matter — according to a new Stanford-led study recently published in Psychology Science

Do the words “steamed green beans” cause your eyes to keep moving down the menu page? Or do you prefer “sizzling Szechuan green beans with toasted garlic”?

People generally prioritize tastiness over health benefits when they choose what to eat. So the researchers investigated whether people can be motivated to eat healthier by highlighting tastiness when naming vegetable dishes.  

“Most strategies to date have focused on getting people to avoid unhealthy foods, in the hope that the promise of health motivates them to eat better,” said Bradley Turnwald, PhD, a postdoctoral fellow in psychology at Stanford and first author of the paper, in a recent Stanford News story. “The problem is, that doesn’t actually motivate most people to approach healthy foods.”

Partnering with the Menus of Change University Research Collaboration, the research team measured the behavior of undergraduate students in self-serve dining halls at five schools around the country for over three months.

They tracked nearly 140,000 food decisions about 71 vegetable dishes that were labeled with a taste-focused, health-focused or neutral name. In a rotating lunch menu, each dining hall served the same vegetable dish on the same day of the week adjacent to the same food choices — changing only the labels.

Taste-focused labels used words that highlighted specific flavors of the ingredients or preparation methods, along with words that suggested a positive experience through excitement, indulgence, tradition or geographic locations.

Health-focused labels communicated the nutritional qualities and health benefits of vegetables. Basic or neutral labels were nondescript. For example, the taste-focused label of “caramelized balsamic and herb vegetable medley” was changed to the health-focused label of “light n’ fit vegetables” or just the basic label of “vegetables.”

The study found that taste-focused labels increased diners’ vegetable selection by 29 percent compared to health-focused labels, and by 14 percent compared with basic labels.

But did the college students eat the vegetables on their plates? The researchers also investigated this question at one of the schools, where they measured by weight the amount of vegetables the students actually consumed. They found the diners ate 39 percent more vegetables when given taste-focused labels compared to health-focused labels.

Taste-focused labeling is about more than just adding appealing adjectives, however. A supplemental study demonstrated that the name needs to be true and to convey specific positive flavor expectations. For instance, the taste-focused “panko parmesan crusted zucchini” outperformed the vaguely-positive “absolutely awesome zucchini.”

“College students have among the lowest vegetable intake rates of all age groups,” said Turnwald in the news article. “Students are learning to make food decisions for the first time in the midst of new stresses, environments and food options. It’s a critical window for establishing positive relationships with healthy eating.”

The researchers are also looking beyond college campuses. In the paper, they suggest that it is time to harness a taste-focused approach to food labeling, nutrition education and cognitive training to overcome the misconception that healthy foods are tasteless and depriving.

Photo by Ewan Munro

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Computer models show promise for personalizing chemotherapy

Computers have revolutionized many fields, so it isn’t surprising that they may be transforming cancer research. Computers are now being used to model the molecular and cellular changes associated with individual tumors, allowing scientists to simulate the tumor’s response to different combinations of chemotherapy drugs.  

Modeling big data to improve personalized cancer treatment was the focus of a recent episode of the Sirius radio show “The Future of Everything.” On hand was Sylvia Plevritis, PhD, a professor of biomedical data science and of radiology at Stanford, who discussed her work with Stanford professor and radio show host Russ Altman, MD, PhD.  

Plevritis and her colleagues are using multi-omics data — including measures of gene expression, protein function, metabolic processes and more — to extensively profile individual tumors of individual patients.

They are analyzing this data to better understand how tumors become drug-resistant. She explained in the podcast that tumors are often heterogeneous — not every cell has the same gene mutations — but chemotherapy drugs typically target specific genetic mutations. Tumors are also driven by complex mechanisms beyond genetic mutations. So her lab is comprehensively characterizing the different cell types in a tumor and how these different cell types respond to individual drugs. By better understanding the complexity of what drives the tumor’s response, they hope to identify the underlying mechanisms of drug resistance.

The goal, Plevritis said, is to more accurately estimate the response of the entire tumor to a given set of drugs without having to run clinical trials on every drug combination. Using their modeling, they hope to identify the most promising drug combinations to make clinical trials more efficient, she said.

The research team tested their computational model by measuring the multi-omics profile of human cancer cells in a dish, before and after exposing the cells to specific drugs. Their model then identified the minimum combination of drugs with the maximum effect. This work used archived cell samples, so their modeling results didn’t impact the patients’ treatment. But they compared their model’s prediction to what drugs the patients actually received.

They determined that the best chemotherapy cocktail for most of the patients would have been just one or two of the drugs that they received. For about 10 percent of the patients, they predicted that a totally different drug would have been the most effective, Plevaritis said in the podcast.

Thus, their computational model may be able to divide patients into different groups, based on tumor characteristics, and match those groups with specific chemotherapy cocktails that would be most effective for them. Plevaritis’ team is currently setting up a study to validate their computational predictions for a group of patients with acute myeloid leukemia, in parallel with a combination drug therapy trial, she said.

As a member of the Cancer Intervention Surveillance Network Modeling consortium, Plevritis is also using computational models to evaluate the impact of cancer screening guidelines — such as the recommended frequency of mammograms for general breast cancer screening — on mortality rates. For example, policy organizations like the U.S. Preventive Service Task Force often ask the consortium to simulate thousands of different screening policies — and rank their potential impact — to use as part of their selection criteria, she said.

One outcome of this work is an online decision tool for women who are at high risk for developing breast cancer because they carry a mutation in the BRCA1 or BRCA2 gene. Plevritis said about 45,000 people worldwide have used the tool, and her team has received a lot of positive feedback.

“It’s been very satisfying to get these emails and this feedback from individuals who feel that this complex information was distilled in a way that they can make sense of it,” Plevritis said.

Image of acute promyelocytic leukemia cells by Ed Uthman

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.