: Alzheimer disease (AD) represents a group of multifactorial disorders characterized by a progressive decline of mental faculties eventually leading to dementia and death. Aging of human populations is behind the rapid worldwide increase in the prevalence of AD in recent decades. AD prevention critically depends on reliable AD-predictive genetic testing but its further development is delicately poised at present. New DNA-analyzing technologies such as the Next Generation Sequencing (NGS) have allowed rapid and comprehensive analysis of the genome and might have aided the research into the genetics of AD. However, discoveries of epigenetic mechanisms and non-coding forms of DNA and RNA - while helping to explain complexities of AD etiologies - have imposed additional challenges onto the AD diagnostics based on DNA analyses. Environmental factors can, via epigenetic mechanisms, modify both coding and non-coding DNA and this has to be respected in DNA testing, including NGS. Risk calculations based on the known odds and risk ratios for selected DNA polymorphisms are viable options at present, while the applications of neural network methodology seems the most promising way forward in the development of predictive AD tests in future.