Posted on Dec 24, 2019, 3 p.m.
The journal Neuron has published a study containing evidence that suggests to refute the link between increased levels of the herpes virus and Alzheimer’s disease, as well as provides a new statistical and computational framework for analysis of large scale sequencing data.
Estimates are that worldwide some 50 million people are affected by Alzheimer’s disease which is a debilitating brain wasting disease that is a progressive dementia resulting in the loss of memory, cognitive abilities as well as verbal skills. Currently there is no known cure, and the numbers of people who are affected by the condition are increasing rapidly.
"Like all types of dementia, Alzheimer's disease is characterized by massive death of brain cells, the neurons. Identifying the reason why neurons begin and continue to die in the brains of Alzheimer's disease patients is an active area of research," said corresponding author Dr. Zhandong Liu, associate professor of pediatrics at Baylor and the Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital.
Certain microbial infections have gained traction as a theory of triggering the disease such as a 2018 study reporting increased levels of HHV-6A and HHV-7 in postmortem brain tissues of over 1,000 patients with AD when compared to healthy aging subjects or those with a different form of neurodegenerative condition; the presence of elevated levels of this genetic material indicated active infections which were linked to the disease. Within a year this study generated much hope and led to several other studies to gain better understandings between the link between viral infections and AD.
When the co-author Dr. Hyun-Hwan and others reanalyzed the data sets from the study using identical statistical methods with rigorous filtering and 4 commonly used statistical tools they were unable to yield the same results. They were motivated to reanalyze because they observed while the p-values were highly significant they were being ascribed to data in which the differences were not visually appreciable. The p-values also did not fit with simple logistic regression, and after several different types of rigorous statistical testing no link was found between the abundance of herpes viral DNA or RNA and likelihood of AD in the cohort.
"As high-throughput 'omics' technologies, which include those for genomics, proteomics, metabolomics and others, become affordable and easily available, there is a rising trend toward 'big data' in basic biomedical research. In these situations, given the massive amounts of data that have to be mined and extracted in a short time, researchers may be tempted to rely solely on p-values to interpret results and arrive at conclusions," Dr. Liu said.
"Our study highlights one of the potential pitfalls of over-reliance on p-values. While p-values are a very valuable statistical parameter, they cannot be used as a stand-alone measure of statistical correlation—data sets from high-throughput procedures still need to be carefully plotted to visualize the spread of the data," Jeong said. "Data sets also have to be used in conjunction with accurately calculated p-values to make gene-disease associations that are statistically correct and biologically meaningful."
"Our goal in pursuing and publishing this study was to generate tools and guidelines for big data analysis, so the scientific community can identify treatment strategies that will likely benefit patients," Liu said.
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