Papers of the Month
By Sara Amolegbe
New algorithm uses medical history to predict Parkinson’s disease
NIEHS-funded researchers developed an algorithm that identifies people with a high probability of being diagnosed with Parkinson’s disease (PD), which is a debilitating movement disorder characterized by tremors, movement slowness, and difficulty with balance and coordination. The predictive model relies on demographic data, as well as medical tests and diagnoses available in Medicare claims data.
Researchers analyzed the Medicare claims of more than 200,000 people to look for associations among a diagnosis of PD, medical conditions, and demographic factors. Using this information, they developed a model that correctly predicted 73 percent of people who would be diagnosed with the disease in 2009, and 83 percent of the people who would not.
Much of the Medicare claims information that helped predict the disease referred to problems known to be associated with PD, such as tremors, posture abnormalities, psychiatric or cognitive dysfunctions, gastrointestinal problems, fatigue, and trauma. Other factors associated with the disease included weight loss and chronic kidney disease. Factors associated with a lower probability of PD included cardiovascular disease, obesity, cancer, gout, and history of tobacco smoking.
According to the authors, this algorithm could provide an early indicator to physicians that patients may need evaluation for the movement disorder. This method may also be used to identify other factors, such as environmental hazards, that may be associated with the disease or have a protective effect.
Citation: Searles Nielsen S, Warden MN, Camacho-Soto A, Willis AW, Wright BA, Racette BA. 2017. A predictive model to identify Parkinson disease from administrative claims data. Neurology 89(14):1448–1456.
Researchers remove noise from metabolomics data
When performing untargeted metabolomics studies, which profile all metabolites in a sample, scientists often detect tens of thousands of signals. These signals were traditionally thought to indicate distinct metabolites. Using a new approach, NIEHS-funded researchers revealed that the actual number of unique metabolites in a typical metabolomics analysis may be close to one-tenth as large as previously thought.
Examining the metabolites in E. Coli, the research team looked for signals that arose from contamination and artifacts, as well as degenerate features, meaning that one metabolite showed up as many different signals. They found thousands of previously unreported degenerate features, with some metabolites showing up as more than 150 signals. Removing these features reduced the number of unique analytes from approximately 25,000 to less than 2961. After removing additional contaminants and other poorly resolved components from the data, they further reduced the number of unique analytes to less than 1000.
This substantial reduction in data was more than five-fold greater than that reported in previously published studies. Based on these results, the authors suggested an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets to help identify the noise. To aid in this effort, they created the creDBle database to provide scientists conducting metabolomics studies with access to annotated reference data sets.
Citation: Mahieu NG, Patti GJ. 2017. Systems-level annotation of a metabolomics data set reduces 25,000 features to fewer than 1000 unique metabolites. Anal Chem 89(19):10397−10406.
Higher manganese levels associated with lower IQ in children
A new NIEHS-funded study revealed that children in East Liverpool, Ohio who had higher levels of manganese (Mn) in their hair had lower IQ scores. East Liverpool, the site of a hazardous waste incinerator and a Mn processor, has exceeded U.S. Environmental Protection Agency reference levels for Mn in the air for more than a decade.
Researchers analyzed blood and hair samples of 106 children, 7 to 9 years of age, from East Liverpool and surrounding communities, from March 2013 to June 2014. Participants and their caregivers received cognitive assessments and questionnaires at the time the samples were taken.
By adjusting for other factors, including lead exposure, the researchers found that increased Mn in hair samples was significantly associated with declines in IQ. Researchers did not see the same association with blood Mn levels, which they noted likely reflected previous findings that suggested that hair Mn might be a better reflection of long-term exposure, whereas Mn levels in blood might best represent current exposure.
This study was conducted in response to a request from the East Liverpool School District superintendent because of concerns about declining academic performance potentially related to high Mn concentrations in the area. According to the authors, community partners were essential to both the conception and implementation of the study.
Citation: Haynes EN, Sucharew H, Hilbert TJ, Kuhnell P, Spencer A, Newman NC, Burns R, Wright R, Parsons PJ, Dietrich KN. 2017. Impact of air manganese on child neurodevelopment in East Liverpool, Ohio. Neurotoxicology; doi: 10.1016/j.neuro.2017.09.001 [Online 6 Sept. 2017].
Flame retardants may impair in vitro fertilization
A higher concentration of some organophosphate flame retardants (PFRs) in urine is associated with negative in vitro fertilization (IVF) outcomes in women, according to an NIEHS-funded study. The findings link exposure to PFRs in women undergoing IVF to a lower probability of embryo fertilization and implantation, as well as fewer successful pregnancies and live births.
Researchers analyzed metabolites of PFRs in urine samples from 211 women who underwent IVF at the Massachusetts General Hospital Fertility Center between 2005 and 2015. PFRs are used in polyurethane foam products and can be found in products such as upholstered furniture, baby supplies, and gym mats. They detected urinary metabolites of three PFRs — bis(1,3-dichloro-2-propyl) phosphate, diphenyl phosphate, and isopropylphenyl phenyl phosphate — in more than 80 percent of participants.
The women with the highest concentrations of PFR metabolites had lower rates of successful fertilization and implantation of the embryo compared with women with the lowest levels of metabolites. Overall, the group with the lowest levels of PFR metabolites had a 41 percent increase in clinical pregnancies and a 38 percent increase in live births, compared with the group with the highest urinary metabolite concentrations.
Citation: Carignan CC, Mínguez-Alarcon L, Butt CM, Williams PL, Meeker JD, Stapleton HM, Toth TL, Ford JB, Hauser R, EARTH Study Team. 2017. Urinary concentrations of organophosphate flame retardant metabolites and pregnancy outcomes among women undergoing in vitro fertilization. Environ Health Perspect 125(8):087018.
(Sara Amolegbe is a research and communication specialist for MDB Inc., a contractor for the NIEHS Division of Extramural Research and Training.)