Discussion as to the factors most commonly responsible for a patient's cognitive improvement.
Insulin resistance is the most common and often the primary underlying trigger of dementia.
The most sensitive and effective way to measure insulin resistance in patients is with a Glucose Tolerance Test that includes insulin measures at fasting, 1-hour and 2-hours at the same times as the glucose measurements.
Extending the Glucose Tolerance Test with a 3-hour and 4-hour Glucose helps establish if the patient has reactive hypoglycemia which is a major risk factor for hypocampal neuron death and progression of dementia.
A more comprehensive and inexpensive assessment of a patients genetic mutations is possible using the “raw data file” from a 23andme.com saliva test and the MTHFRsupport.com report. This goes way beyond EPOe4 and MTHFR mutations.
Understanding where the genetic mutations are gives us specific understanding on how to improve the downstream biochemical impairments related to each mutation.
It's important to understand that sensitivity to various toxins and exposure to chronic low grade infections lead to chronic inflammation and therefore greater insulin resistance.
Testing for mycotoxins, glyphosate, industrial toxin load and heavy metals is a critical step in helping patients restore cognitive function.
Cytox launched their test, “The Alzheimer's Risk Test – powered by genoSCORE” into North America late 2021, led by their testing laboratory partners, Sampled.
The Alzheimer's Risk Test is a Polygenic Risk Scoring (PRS) test that provides a comprehensive assessment of genetic risk linked to late-onset Alzheimer's disease and associated cognitive decline.
Alzheimer's disease is a highly complex disease with risk factors based in genetics, lifestyle, age, and environment but up to 50% of the risk factors are modifiable and so can be addressed to reduce overall risk.
The Alzheimer's Risk Test is offered by approved clinical practices and requires only a simple saliva sample and uses a Polygenic Risk algorithm to predict the risk of individuals developing Alzheimer's disease and so optimise clinical management of those at highest risk.