Posted on by Dr. Francis Collins
As research on Alzheimer’s disease (AD) advances, a desperate need remains for an easy blood test to help diagnose the condition as early as possible. Ideally, such a test could also distinguish AD from other forms of dementia that produce similar symptoms. As published recently in Nature Medicine, an NIH-funded research team has designed a simple blood test that is on course to meet these criteria .
The latest work builds on a large body of work showing that one secret to predicting a person’s cognitive decline and treatment response in AD lies in a protein called tau. Using the powerful, but expensive, approach of PET scan imaging, we know that tau builds up in the brain as Alzheimer’s disease progresses. We also know that some tau spills from the brain into the bloodstream.
The trouble is that the circulating tau protein breaks down far too quickly for a blood test to offer a reliable measure of what’s happening in a person’s brain. A few years ago, researchers discovered a possible solution: test for blood levels of a slightly different and more stable version of the protein called pTau181 . (The “p” in its name comes from the addition of phosphorus in a particular part of the protein’s structure.)
In the latest study, researchers in the lab of Adam Boxer, University of California, San Francisco, followed up further on this compelling lead. Boxer’s team measured pTau181 levels in blood samples from 362 people between the ages of 58 and 70. Those samples included 56 people with an Alzheimer’s diagnosis, along with 47 people with mild cognitive impairment and 69 healthy controls.
The researchers also included another 190 people diagnosed with frontotemporal lobar degeneration (FTLD). It is a relatively rare form of dementia that leads to a gradual decline in behavior, language, and movement, often in connection with a buildup of tau in the brain.
The study found that levels of pTau181 were roughly 3.5-times higher in the blood of people with AD compared to people without AD. Those with mild cognitive impairment due to underlying AD also showed an intermediate increase in blood levels of pTau181.
Importantly, people with FLTD had normal blood levels of pTau181. As a result, the blood test could reliably distinguish between a person with AD and a person with FLTD. That’s important because, while FLTD is a relatively rare condition, its prevalence is similar to AD in people under the age of 65. But both conditions have similar symptoms, making it often challenging to distinguish them.
The findings add to evidence that the new blood test can help in diagnosing AD and in distinguishing it from other neurodegenerative conditions. In fact, it does so with an accuracy that often rivals more expensive PET scans and more invasive cerebrospinal fluid tests, which are now the only reliable ways to measure tau.
There’s still plenty of work to do before this blood test is ready for a doctor’s office. But these initial findings are very promising in helping to simplify the diagnosis of this devastating condition that now affects an estimated 5.5 million Americans .
 Diagnostic value of plasma phosphorylated tau181 in Alzheimer’s disease and frontotemporal lobar degeneration. Thijssen EH, La Joie R, Wolf A, Strom A, Wang P, Iaccarino L, Bourakova V, Cobigo Y, Heuer H, Spina S, VandeVrede L, Chai X, Proctor NK, Airey DC, Shcherbinin S, Duggan Evans C, Sims JR, Zetterberg H, Blennow K, Karydas AM, Teunissen CE, Kramer JH, Grinberg LT, Seeley WW, Rosen H, Boeve BF, Miller BL, Rabinovici GD, Dage JL, Rojas JC, Boxer AL; Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) investigators. Nat Med. 2020 Mar 2.
 Plasma phospho-tau181 increases with Alzheimer’s disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Mielke MM, Hagen CE, Xu J, Chai X, Vemuri P, Lowe VJ, Airey DC, Knopman DS, Roberts RO, Machulda MM, Jack CR Jr, Petersen RC, Dage JL. Alzheimers Dement. 2018 Aug;14(8):989-997.
 Alzheimer’s Disease Fact Sheet. National Institute on Aging, May 22, 2019.
Alzheimer’s Disease & Related Dementias (National Institute on Aging/NIH)
Adam Boxer (University of California, San Francisco)
NIH Support: National Institute on Aging; National Institute of Neurological Disorders and Stroke; National Center for Advancing Translational Sciences
Posted on by Dr. Francis Collins
Back in April 2003, when the international Human Genome Project successfully completed the first reference sequence of the human DNA blueprint, we were thrilled to have achieved that feat in just 13 years. Sure, the U.S. contribution to that first human reference sequence cost an estimated $400 million, but we knew (or at least we hoped) that the costs would come down quickly, and the speed would accelerate. How far we’ve come since then! A new study shows that whole genome sequencing—combined with artificial intelligence (AI)—can now be used to diagnose genetic diseases in seriously ill babies in less than 24 hours.
Take a moment to absorb this. I would submit that there is no other technology in the history of planet Earth that has experienced this degree of progress in speed and affordability. And, at the same time, DNA sequence technology has achieved spectacularly high levels of accuracy. The time-honored adage that you can only get two out of three for “faster, better, and cheaper” has been broken—all three have been dramatically enhanced by the advances of the last 16 years.
Rapid diagnosis is critical for infants born with mysterious conditions because it enables them to receive potentially life-saving interventions as soon as possible after birth. In a study in Science Translational Medicine, NIH-funded researchers describe development of a highly automated, genome-sequencing pipeline that’s capable of routinely delivering a diagnosis to anxious parents and health-care professionals dramatically earlier than typically has been possible .
While the cost of rapid DNA sequencing continues to fall, challenges remain in utilizing this valuable tool to make quick diagnostic decisions. In most clinical settings, the wait for whole-genome sequencing results still runs more than two weeks. Attempts to obtain faster results also have been labor intensive, requiring dedicated teams of experts to sift through the data, one sample at a time.
In the new study, a research team led by Stephen Kingsmore, Rady Children’s Institute for Genomic Medicine, San Diego, CA, describes a streamlined approach that accelerates every step in the process, making it possible to obtain whole-genome test results in a median time of about 20 hours and with much less manual labor. They propose that the system could deliver answers for 30 patients per week using a single genome sequencing instrument.
Here’s how it works: Instead of manually preparing blood samples, his team used special microbeads to isolate DNA much more rapidly with very little labor. The approach reduced the time for sample preparation from 10 hours to less than three. Then, using a state-of-the-art DNA sequencer, they sequence those samples to obtain good quality whole genome data in just 15.5 hours.
The next potentially time-consuming challenge is making sense of all that data. To speed up the analysis, Kingsmore’s team took advantage of a machine-learning system called MOON. The automated platform sifts through all the data using artificial intelligence to search for potentially disease-causing variants.
The researchers paired MOON with a clinical language processing system, which allowed them to extract relevant information from the child’s electronic health records within seconds. Teaming that patient-specific information with data on more than 13,000 known genetic diseases in the scientific literature, the machine-learning system could pick out a likely disease-causing mutation out of 4.5 million potential variants in an impressive 5 minutes or less!
To put the system to the test, the researchers first evaluated its ability to reach a correct diagnosis in a sample of 101 children with 105 previously diagnosed genetic diseases. In nearly every case, the automated diagnosis matched the opinions reached previously via the more lengthy and laborious manual interpretation of experts.
Next, the researchers tested the automated system in assisting diagnosis of seven seriously ill infants in the intensive care unit, and three previously diagnosed infants. They showed that their automated system could reach a diagnosis in less than 20 hours. That’s compared to the fastest manual approach, which typically took about 48 hours. The automated system also required about 90 percent less manpower.
The system nailed a rapid diagnosis for 3 of 7 infants without returning any false-positive results. Those diagnoses were made with an average time savings of more than 22 hours. In each case, the early diagnosis immediately influenced the treatment those children received. That’s key given that, for young children suffering from serious and unexplained symptoms such as seizures, metabolic abnormalities, or immunodeficiencies, time is of the essence.
Of course, artificial intelligence may never replace doctors and other healthcare providers. Kingsmore notes that 106 years after the invention of the autopilot, two pilots are still required to fly a commercial aircraft. Likewise, health care decisions based on genome interpretation also will continue to require the expertise of skilled physicians.
Still, such a rapid automated system will prove incredibly useful. For instance, this system can provide immediate provisional diagnosis, allowing the experts to focus their attention on more difficult unsolved cases or other needs. It may also prove useful in re-evaluating the evidence in the many cases in which manual interpretation by experts fails to provide an answer.
The automated system may also be useful for periodically reanalyzing data in the many cases that remain unsolved. Keeping up with such reanalysis is a particular challenge considering that researchers continue to discover hundreds of disease-associated genes and thousands of variants each and every year. The hope is that in the years ahead, the combination of whole genome sequencing, artificial intelligence, and expert care will make all the difference in the lives of many more seriously ill babies and their families.
 Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation. Clark MM, Hildreth A, Batalov S, Ding Y, Chowdhury S, Watkins K, Ellsworth K, Camp B, Kint CI, Yacoubian C, Farnaes L, Bainbridge MN, Beebe C, Braun JJA, Bray M, Carroll J, Cakici JA, Caylor SA, Clarke C, Creed MP, Friedman J, Frith A, Gain R, Gaughran M, George S, Gilmer S, Gleeson J, Gore J, Grunenwald H, Hovey RL, Janes ML, Lin K, McDonagh PD, McBride K, Mulrooney P, Nahas S, Oh D, Oriol A, Puckett L, Rady Z, Reese MG, Ryu J, Salz L, Sanford E, Stewart L, Sweeney N, Tokita M, Van Der Kraan L, White S, Wigby K, Williams B, Wong T, Wright MS, Yamada C, Schols P, Reynders J, Hall K, Dimmock D, Veeraraghavan N, Defay T, Kingsmore SF. Sci Transl Med. 2019 Apr 24;11(489).
DNA Sequencing Fact Sheet (National Human Genome Research Institute/NIH)
Genomics and Medicine (NHGRI/NIH)
Genetic and Rare Disease Information Center (National Center for Advancing Translational Sciences/NIH)
Stephen Kingsmore (Rady Children’s Institute for Genomic Medicine, San Diego, CA)
NIH Support: National Institute of Child Health and Human Development; National Human Genome Research Institute; National Center for Advancing Translational Sciences
Posted on by Dr. Francis Collins
Credit: Wellcome Centre for Human Neuroimaging, University College London.
In recent years, researchers fueled by the BRAIN Initiative and many other NIH-supported efforts have made remarkable progress in mapping the human brain in all its amazing complexity. Now, a powerful new imaging technology promises to further transform our understanding . This wearable scanner, for the first time, enables researchers to track neural activity in people in real-time as they do ordinary things—be it drinking tea, typing on a keyboard, talking to a friend, or even playing paddle ball.
This new so-called magnetoencephalography (MEG) brain scanner, which looks like a futuristic cross between a helmet and a hockey mask, is equipped with specialized “quantum” sensors. When placed directly on the scalp surface, these new MEG scanners can detect weak magnetic fields generated by electrical activity in the brain. While current brain scanners weigh in at nearly 1,000 pounds and require people to come to a special facility and remain absolutely still, the new system weighs less than 2 pounds and is capable of generating 3D images even when a person is making motions.
Posted on by Dr. Francis Collins
You expect to have your blood pressure checked and treated when you visit the doctor’s office or urgent care clinic. But what about the barbershop? New research shows that besides delivering the customary shave and a haircut, barbers might be able to play a significant role in helping control high blood pressure.
High blood pressure, or hypertension, is a particularly serious health problem among non-Hispanic black men. So, in a study involving 52 black-owned barbershops in the Los Angeles area, barbers encouraged their regular, black male patrons, ages 35 to 79, to get their blood pressure checked at their shops . Nearly 320 men turned out to have uncontrolled hypertension and enrolled in the study. In a randomized manner, barbers then encouraged these men to do one of two things: attend one-on-one barbershop meetings with pharmacists who could prescribe blood pressure medicines, or set up appointments with their own doctors and consider making lifestyle changes.
The result? More than 63 percent of the men who received medications prescribed by specially-trained pharmacists lowered their blood pressure to healthy levels within 6 months, compared to less than 12 percent of those who went to see their doctors. The findings serve as a reminder that helping people get healthier doesn’t always require technological advances. Sometimes it may just involve developing more effective ways of getting proven therapy to at-risk communities.