Type 2 diabetes (T2D) and Alzheimer's disease (AD) are complex diseases commonly associated with aging.
Accumulating evidence indicates a connection between these two diseases at the molecular level. Much of what we
currently know about T2D and AD is derived from in vivo and in vitro studies. However, further research and
characterization of molecules is necessary to establish a strong connection between T2D and AD. In silico studies play a
major role in finding non-evident patterns of gene expression and gene network connectivity. In this review, we give a
brief introduction to T2D and AD and then describe the risk factors and molecules that are commonly associated with
these diseases. Finally, we discuss the future directions and applications of bioinformatics that can provide greater insight
into the relationship between these two diseases. Analysis and integration of high-throughput data on genomics,
transcriptomics, proteomics and metabolomics from normal and disease tissues would be very useful to improve our
understanding of the mechanism behind disease initiation and the connection between these two diseases. We encourage
researchers to use bioinformatics approaches to identify genes and their regulatory pathways that are commonly affected
in T2D and AD, as these genes and pathways could be potential biomarkers and targets for disease treatment.
Keywords: Type 2 diabetes, Alzheimer's disease, bioinformatics, high-throughput sequencing data.
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