The Observatory

Oct. 24, 2017

Influenza by the numbers

5 to 20
is the percentage of the U.S. population that gets the flu each year.

2 to 7
is the number of days influenza symptoms last.

$10.4 billion
is the annual cost of influenza in direct medical expenses.

$16.3 billion
is the annual cost of influenza in lost earnings.

31.4 million
is the annual number of outpatient visits due to flu in the U.S.

is the annual number of hospitalizations due to flu in the U.S.

is the annual percentage of children aged 6 months to 17 years who receive an influenza vaccination.

is the annual percentage of adults aged 18-49 who receive an influenza vaccination.

is the annual percentage of adults aged 50-64 who receive an influenza vaccination.

is the annual percentage of adults aged 65+ who receive an influenza vaccination.

Sources:,, and

Molecular Diagnostics

Doctors can now predict the severity of disease by measuring molecules. An international team of researchers has found a way to diagnose disease and predict patient outcomes simply by measuring extremely small changes in interactions among molecules inside the body. The new technique could offer vastly superior predictions of disease severity in a huge range of conditions with a genetic component, such as Alzheimer’s, autism, cancer, cardiovascular disease, diabetes, obesity, schizophrenia, and depression.

Gene mutations that cause disease physically alter the interactions of molecules that cells use to communicate with one another. Until now, scientists have had no easy way to measure the subtle changes in these interaction forces. But researcher J. Julius Zhu, PhD, of the University of Virginia School of Medicine, and his collaborators have developed a method to accurately and efficiently calculate these tiny changes. It’s a feat that requires incredible precision: Force is typically measured in newtons—the amount of force needed to accelerate one kilogram of mass one meter per second squared—but Zhu’s technique measures on a scale of piconewtons—that is, one trillionth of a newton.

Zhu and colleagues have used the new technique to show that gene mutations responsible for mental-health diseases change molecular interactions by a few piconewtons. These small changes then have a tremendous ripple effect. The researchers found the molecular changes lead to harmful changes in how the cells communicate—and ultimately, in cognitive ability. By measuring the molecular changes, the scientists could predict the resulting cognitive impairment.

Zhu’s approach represents a new use for a high-tech scientific instrument called “optical tweezers” that uses a highly focused laser to hold and move microscopic objects. Using the optical tweezers, scientists can measure the force required to break up intermolecular bonds among the signaling molecules inside the body, allowing them gauge the effects of gene mutations in patients.

Quality Control

CAP releases 2017 Laboratory Accreditation Program checklists to improve laboratory quality. The College of American Pathologists (CAP) has released the 2017 edition of its Laboratory Accreditation Program checklists. The checklists contain approximately 3,000 requirements that are used during laboratory accreditation inspections to help laboratories stay in compliance with the Centers for Medicare and Medicaid Services (CMS) regulations.

The CMS regulates all laboratory testing, except research, performed on humans in the United States through the Clinical Laboratory Improvement Amendments (CLIA). The CAP is a CMS-approved accreditation organization with deeming authority to inspect laboratories under CLIA.

The CAP’s program is based on rigorous accreditation standards that are translated into detailed checklist requirements. CAP inspection teams use the checklists as a guide to assess the laboratory’s overall management and operation. The program is internationally recognized and is the largest of its kind that utilizes teams of practicing laboratory professionals as inspectors.

As with each yearly checklist edition, the CAP reviews all 21 discipline-specific checklists to maintain program stringency and the highest standards of patient care while reflecting advancements in medicine, technology, and laboratory management. The CAP Checklists Committee, made up of practicing pathologist members, leads the annual review and updating of checklists, seeking input from experts in pathology and laboratory medicine.

In the 2017 accreditation checklist edition, the “Team Leader Checklist” has been renamed “Director Assessment Checklist,” to better reflect the checklist’s intent of assessing the laboratory director. The CAP made some of the most significant changes to checklists for the sections on personnel, specimen collection and handling, laboratory director responsibility and oversight, anatomic pathology, and molecular-based testing.


Variation in genetic risk explains which people develop type 1 diabetes in later life. Having certain genetic variants could explain why people can develop type 1 diabetes at markedly different ages, including later in life, says new research recently presented at this year’s annual meeting of the European Association for the Study of Diabetes (EASD) in Lisbon, Portugal. The study is the first to suggest there is a specific genetic predisposition for late onset type 1 diabetes.

Type 1 diabetes (T1D) is caused by an autoimmune attack in the body killing off the insulin-producing beta cells in the pancreas, eventually leaving most people with a lifelong dependency on insulin. It typically affects children and young adults but can affect patients after the age of 30 years (referred to as late onset T1D).

Certain groups of genes associated with regulation of the immune system in humans are known to be linked to the risk of developing T1D. The major genetic determinants are the DR3 and DR4 alleles (or variants) of a group of genes called the HLA complex. The strongest risk occurs when these risk alleles occur in pairs which can either be homozygous (DR3/DR3 or DR4/DR4), or compound heterozygous (DR3/DR4) genotypes.

The research team, from the University of Exeter UK, aimed to investigate whether the increased risk of T1D that is observed in children and young adults with the DR3 and DR4 genotypes persists into adulthood. The scientists analyzed the development of T1D diabetes in a population of 120,000 individuals from the UK Biobank from birth to age 60 in subjects selected from the highest risk HLA groups. They found that although the highest risk genotypes made up just 6.4 percent of the population of the United Kingdom, they contributed 61 percent of all cases of T1D. Within these high-risk groups there were marked differences in both the likelihood of developing T1D and the average age of diagnosis.

In the high-risk HLA groups DR3/DR3, DR3/DR4, and DR4/DR4, there were marked differences in likelihood of developing T1D during a person’s lifetime: 1.2 percent, 4.2 percent, and 3.5 percent respectively. For the DR3/DR3, DR3/DR4, and DR4/DR4 genotypes, the mean age of diagnosis was 17, 28, and 38 years old respectively, with 71 percent of T1D cases associated with the DR4/DR4 genotype being diagnosed in individuals over 30. For DR3/DR3/ just 26 percent were diagnosed over 30, while for DR3/DR4 the figure was 40 percent.

Drugs of Abuse

CDC awards $28.6 million to help states fight opioid overdose epidemic. The U.S. Centers for Disease Control and Prevention (CDC) is awarding more than $28.6 million in additional funding to 44 states and the District of Columbia to support their responses to the opioid overdose epidemic. The funds will be used to strengthen prevention efforts and better track opioid-related overdoses. This builds upon the July 2017 announcement that CDC was providing $12 million to states to support overdose prevention activities.

Increased funding for opioids in the fiscal year (FY) 2017 Omnibus Appropriations bill is allowing the CDC to support all states funded under its Overdose Prevention in States (OPIS) effort, which includes three programs that equip states with resources needed to address the epidemic. The programs are Prescription Drug Overdose: Prevention for States (PfS); Data-Driven Prevention Initiative (DDPI); and Enhanced State Opioid Overdose Surveillance (ESOOS).

Under the PfS program, $19.3 million in funding will go to 27 states in program expansion supplemental awards. Under the DDPI, $4.6 million in funding will go to 12 states and Washington, DC. Funds will be used by states to scale up prevention activities that include increasing the use of prescription drug monitoring programs and improving clinical feedback from these systems, expanding the reach of messages about the risks associated with opioids, and other practices such as conducting overdose fatality reviews to improve prevention efforts.

Under the ESOOS program, $4.7 million will go to 32 states and Washington, DC, to better track and prevent opioid-involved nonfatal and fatal overdoses. Funds will be used by states to directly support medical examiners and coroners, including funds for comprehensive toxicology testing and for enhancing their surveillance activities.


A new genetic marker for schizophrenia? Schizophrenia is a complicated disease that often appears in early adulthood. Although scientists have not traced the genetic causes, more than 80 percent of schizophrenia cases are considered to have a hereditary cause. In a new report published in Translational Psychiatry, Japanese researchers report that a rare genetic variant, RTN4R, may have a fundamental role in the disease.

“Schizophrenia is a disease caused by disturbances in neural circuits. Myelin-related genes are associated with the disease,” explains Osaka University Professor Toshihide Yamashita, one of the study authors.

Myelin acts as a conductor of signals for the neural circuits. Yamashita hypothesized that myelin-related genes could contribute to the pathology of schizophrenia. RTN4R is a subunit of RTN4, which regulates crucial functions for neural circuits, namely, axon regeneration and structural plasticity. Moreover, “RTN4 is a promising candidate gene for schizophrenia because it is located at chromosome 22q11.2, a hotspot for schizophrenia,” he says.

Rare variants describe mutations that have low frequency but a large effect. Yamashita and colleagues searched for rare variants of RTN4. Screening the DNA of 370 schizophrenia patients, they found a single missense mutation, R292H, that changed the amino acid of this protein from arginine to histidine in two patients.

R292H is located in the domain of RTN4R that binds to ligands, so a change in even a single amino acid could have profound effects on RTN4 function. To test this possibility, the scientists expressed the mutation in chick retinal cells, which only weakly express the gene, finding a significant change in myelin-dependent axonal behavior. Computer simulations showed that the mutation reduced the interaction between RTN4 and its partner protein, LINGO1, by increasing the distance between the two.

“There is growing evidence that rare variants contribute to neurodevelopment diseases,” says Yamashita. The R292H mutation was not found in any existing databases. Our findings strengthen the evidence that rare variants could contribute to schizophrenia.”

Personalized Medicine

Researchers identify potential biomarkers of age-related macular degeneration. Patients with any stage of age-related macular degeneration (AMD) carry signs of the disease in their blood that may be found through special laboratory tests, according to a new study led by AMD researchers based at Massachusetts Eye and Ear. The study uses metabolomics to identify blood profiles associated with AMD and its level of severity. These potential lipid biomarkers in human blood plasma may lead to earlier diagnosis, better prognostic information, and more precise treatment, as well as potential new targets for treatment.

“The study utilized metabolomics, or the study of the tiny particles called metabolites in our body that reflect our genes and environment,” explains first author Ines Lains, MD. “The metabolome—the set of metabolites present in an individual—is thought to closely represent the true functional state of complex diseases. This is why we used it to test 90 blood samples obtained from participants with all stages of AMD (30 with early-stage disease, 30 with intermediate-stage and 30 with late-stage) and 30 from patients without AMD.”

Their study revealed 87 metabolites that were significantly different between subjects with AMD and those without. The team also noted varying characteristics between the blood profiles of each stage of disease. Of the 87 molecules identified as associated with AMD, most belonged to the lipid pathway. In fact, six of the seven most significant metabolites identified in the study were lipids. Previous research has suggested that lipids may be involved in the development of AMD, although their exact role in the disease process is unclear.