Introduction: Type 2 diabetes mellitus (T2DM) is a risk factor for Alzheimer's disease. Cerebrospinal fluid (CSF) amyloid β (Aβ) 1‐42 is an important Alzheimer's disease biomarker. However, it is inconclusive on how T2DM is related to CSF Aβ1‐42.Methods: Participants with T2DM were selected from the Alzheimer's Disease Neuroimaging Initiative by searching keywords from the medical history database. A two‐way analysis of covariance model was used to analyze how T2DM associates with CSF Aβ1‐42 or cerebral cortical Aβ.Results: CSF Aβ1‐42 was higher in the T2DM group than the nondiabetic group. The inverse relation between CSF Aβ1‐42 and cerebral cortical Aβ was independent of T2DM status. Participants with T2DM had a lower cerebral cortical Aβ in anterior cingulate, precuneus, and temporal lobe than controls.Discussion: T2DM is positively associated with CSF Aβ1‐42 but negatively with cerebral cortical Aβ. The decreased cerebral cortical Aβ associated with T2DM is preferentially located in certain brain regions.

Background: Alzheimer disease and related dementias (AD/RD) are progressive neurocognitive disorders that currently affect approximately 50 million people worldwide. Mobile phone apps have been well-integrated into daily lives and can be used to deliver and promote health care. There is an increase in the use of technology to provide care and support to AD/RD patients and their families. Objective: This study aimed to review apps designed for AD/RD patients and analyze the benefits of, and challenges to, such technological solutions. Methods: A systematic approach was applied to review the availability, content, features, and quality of mobile phone apps to support self-care among AD/RD patients. Results: The initial search for this review was conducted in January 2019, and the screening and analysis of the included apps were completed in May 2019. A total of 14 apps were included from an initial search of 245 apps. The top 3 features were alert (9/14, 64%), self-care tips (6/14, 42%), and social networking capacity (5/14, 35%). On average, the readability of the apps was a tenth-grade reading level (SD 3.06). The overall quality was 3.71 out of 5 (SD 1.37). Conclusions: Our findings suggest that currently available apps for AD/RD patients may not meet complex needs and may be challenging to use, given the possible impaired communication ability associated with AD/RD. Therefore, high-quality apps need to be developed and rigorously evaluated for feasibility and efficacy.

Long COVID (LongC) is associated with a myriad of symptoms including cognitive impairment. We reported at the beginning of the COVID-19 pandemic that neuronal-enriched or L1CAM+ extracellular vesicles (nEVs) from people with LongC contained proteins associated with Alzheimer’s disease (AD). Since that time, a subset of people with prior COVID infection continue to report neurological problems more than three months after infection. Blood markers to better characterize LongC are elusive. To further identify neuronal proteins associated with LongC, we maximized the number of nEVs isolated from plasma by developing a hybrid EV Microfluidic Affinity Purification (EV-MAP) technique. We isolated nEVs from people with LongC and neurological complaints, AD, and HIV infection with mild cognitive impairment. Using the OLINK platform that assesses 384 neurological proteins, we identified 11 significant proteins increased in LongC and 2 decreased (BST1, GGT1). Fourteen proteins were increased in AD and forty proteins associated with HIV cognitive impairment were elevated with one decreased (IVD). One common protein (BST1) was decreased in LongC and increased in HIV. Six proteins (MIF, ENO1, MESD, NUDT5, TNFSF14 and FYB1) were expressed in both LongC and AD and no proteins were common to HIV and AD. This study begins to identify differences and similarities in the neuronal response to LongC versus AD and HIV infection.

Background: Diabetes has been shown as a risk factor for cognitive impairments. However, it is still not clear about the time course of developing abnormal cognition in those with diabetes especially if the morbidity accelerates the cognitive deterioration process. Objective: To study how diabetes is related to the abnormal cognition development. Methods: A retrospective analysis was performed using data collected by the National Alzheimer’s Coordinating Center. Incidence, prevalence, and age at onset (AAO) of either mild cognitive impairment (MCI) or dementia were compared between participants with and without diabetes. Results: During a follow-up period of more than 10 years, the diabetic group had a higher incidence and prevalence of MCI or dementia than the non-diabetic group. However, the AAO of either MCI or dementia was independent of the diagnosis of diabetes. Conclusion: Although diabetic patients have a higher incidence and prevalence of abnormal cognition than those without diabetes, diabetes does not accelerate the cognitive deterioration process.