Blood offers promise as a way to detect Alzheimer’s disease at its earliest onset, Mayo Clinic researchers say. They envision a test that would detect distinct metabolic signatures in blood plasma that are synonymous with the disease — years before patients begin showing cognitive decline. Their study was recently published online in the journal PLOS ONE.Researchers analyzed cerebrospinal fluid and plasma samples from 45 people in the Mayo Clinic Study on Aging and Mayo Clinic Alzheimer’s Disease Center (15 with no cognitive decline, 15 with mild cognitive impairment and 15 with Alzheimer’s disease). They detected significant changes in the cerebrospinal fluid and plasma in those with cognitive decline and Alzheimer’s. Most important, changes in plasma accurately reflected changes in the cerebrospinal fluid, validating blood as a reliable source for the biomarker development. The team uses a relatively new technique called metabolomics, which measures the chemical fingerprints of metabolic pathways in the cell — sugars, lipids, nucleotides, amino acids and fatty acids — to detect the changes. Metabolomics assesses what is happening in the body at a given time and at a fine level of detail, giving scientists insight into the cellular processes that underlie a disease. In this case, the metabolomic profiles showed changes in metabolites related to mitochondrial function and energy metabolism, further confirming that altered mitochondrial energetics is at the root of the disease process.
The basic concept here is that a disease, Alzheimer's disease in this example, causes changes in the body's metabolic pathways. These changes are referred to as "chemical fingerprints" in the article quoted above or, perhaps more clearly, as "altered metabolic pathways." Historically, we have often looked at variations of a single analyte or small sets of them to diagnose disease. For example, serum glucose might be sky-high for a diabetic patient or PSA may be elevated in a patient with cancer of the prostate. Metabolomics allows the diagnostician and labs to look at complex metabolic pathways for a patient and detect the subtle, but significant, changes of common metabolites. Such analyses obviously requires powerful computer support to both identify the subtle changes that are associated with a particular disease and then detect them later in patients suspected of perhaps being in an early state of that disease.