Early Detection Biomarkers Found Using Blood and Urine Samples

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Researchers have discovered biomarkers in blood and urine that indicate possible early signs of Parkinson’s Disease. Using data, blood, and urine samples from the Biobank in the United Kingdom (UK) across England, Scotland, and Wales.

Researchers have discovered and identified thirteen blood biomarkers associated with the disease from sixty-seven biomarkers, four from urine samples, and sixty-three from blood samples. The study incorporated samples from a total of 502,357 individuals, excluding patients diagnosed with Parkinson’s within three years of the study. The UK Biobank data includes information from over a half-million individuals who attended twenty-two assessment centers, completing questionaries, and participating in interviews with staff. 

Blood and urine tests are used by doctors to diagnose potential illnesses a patient may have. A Complete Blood Count, or CBC, is the most common test performed, usually as part of a routine check-up.  A CBC evaluates red and white blood cell counts, along with platelet, hemoglobin, and hematocrit levels. A urinalysis assesses acidity, protein, glucose, white blood cells, bilirubin (a byproduct of red blood cells breaking down), and blood levels and is evaluated based on color, cloudiness, and concentration. A test strip used to collect a specimen will undergo a chemical analysis, and urine examined under a microscope will be checked for signs of bacteria by a medical laboratory technician. 

Parkinson’s Disease is a neurological disorder, with up to ninety thousand people diagnosed each year. The disease affects the brain’s ability to control physical movement due to the loss of dopamine, causing symptoms like tremors, slowed movement, and balance problems. It can also cause non-movement disorders such as mood disorders and sleep disturbances.  

Modeling

The study was built using three models. The first model used data based on sex, the participant’s age, physical activities of each individual, smoking, alcohol consumption, and education. Model Two took into account variables such as diabetes, hypertension, and stroke that are linked to neurological health. For Model Three; Researchers took data from both models one and two and using Multivariable Cox Regression  (A mathematical or statistical technique that examines a group of variables and their relationship with the timing or occurrence of an event over time), performed an analysis that was able to narrow the results to thirteen separate biomarkers, each on their own related to the onset of Parkinson’s disease. 

Researchers also obtained and analyzed aggregated data from the IEU Open GWAS Project (Genome-Wide Association Study (GWAS)). Data from the study was processed through a computerized command line tool called LD Score Regression (LDSC) and Genome-wide Complex Trait Analysis (GNOVA), software designed to estimate relationships between unrelated individuals using genome-wide single nucleotide polymorphism (SNP) data. Genome-wide single nucleotide polymorphism (SNP) refers to variations in a single DNA building block across the entire genome occurring at specific positions in the DNA sequence and can influence traits, diseases, and genetic diversity among individuals.  An analysis of eleven of these biomarkers found genetic relationships with Parkinson’s disease in six of the samples that were tested as part of the research into looking for biomarkers in blood and urine samples.

The study focused mainly on caucasian study participants within the UK, with researchers admitting that the results limit their findings to other demographic groups. British individuals make up 94.1 percent of the UK’s Biobank; however, researchers are confident that the sample size is large enough to back up the data and present reliable conclusions based on the research. Future data will need to include a more diverse population sample in order to be able to offer comparable results with other segments of the globe to understand how blood and urine biomarkers can play a role in the early detection of Parkinson’s disease.

Much more detail about these findings can be read here at Nature Partner Journals