Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts.

Machine learning (ML) is becoming an integral aspect of several domains in medicine. Yet, most pathologists and laboratory professionals remain unfamiliar with such tools and are unprepared for their inevitable integration. To bridge this knowledge gap, we present an overview of key elements within this emerging data science discipline. First, we will cover general, well-established concepts within ML, such as data type concepts, data preprocessing methods, and ML study design. We will describe common supervised and unsupervised learning algorithms and their associated common machine learning terms (provided within a comprehensive glossary of terms that are discussed within this review). Overall, this review will offer a broad overview of the key concepts and algorithms in machine learning, with a focus on pathology and laboratory medicine. The objective is to provide an updated useful reference for those new to this field or those who require a refresher.

DNA methylation of TOMM40-APOE-APOC2 in Alzheimer's disease.

The apolipoprotein E (APOE) ε4 allele is the major genetic risk factor for Alzheimer's disease (AD). Multiple regulatory elements, spanning the extended TOMM40-APOE-APOC2 region, regulate gene expression at this locus. Regulatory element DNA methylation changes occur under different environmental conditions, such as disease. Our group and others have described an APOE CpG island as hypomethylated in AD, compared to cognitively normal controls. However, little is known about methylation of the larger TOMM40-APOE-APOC2 region. The hypothesis of this investigation was that regulatory element methylation levels of the larger TOMM40-APOE-APOC2 region are associated with AD. The aim was to determine whether DNA methylation of the TOMM40-APOE-APOC2 region differs in AD compared to cognitively normal controls in post-mortem brain and peripheral blood. DNA was extracted from human brain (n = 12) and peripheral blood (n = 67). A methylation array was used for this analysis. Percent methylation within the TOMM40-APOE-APOC2 region was evaluated for differences according to tissue type, disease state, AD-related biomarkers, and gene expression. Results from this exploratory analysis suggest that regulatory element methylation levels within the larger TOMM40-APOE-APOC2 gene region correlate with AD-related biomarkers and TOMM40 or APOE gene expression in AD.