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Last Posted: May 28, 2023
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How one man's rare Alzheimer’s mutation delayed the onset of disease Genetic resilience found in a person predisposed to early-onset dementia could potentially lead to new treatments.
S Reardon, Nature, May 16, 2023

The researchers found that the man had a mutation in a gene coding for a protein called reelin, which is associated with brain disorders including schizophrenia and autism. Little is known about reelin’s role in Alzheimer’s. The study challenges the theory that Alzheimer’s disease is primarily driven by amyloid plaques, which are the targets of several drugs recently approved by the US Food and Drug Administration. The drugs effectively remove amyloid from the brain, but lead to only a moderate improvement in rates of cognitive decline.

'It Totally Backfired': The Pitfalls of Alzheimer's Genetic Testing
J Steenhuysen, Medscape, April 24, 2023

Testing for the APOE4 gene variant among Americans being treated for Alzheimer's has more than doubled from a year ago. The increase was driven by the new treatments that promise to slow the progression of the disease, but also carry risks, especially for people like Nelson carrying two copies of APOE4. Yet few support services are available to help people deal with the implications of APOE4 testing, according to interviews with more than a dozen neurologists and genetic counselors.

Evaluation of Plasma Biomarkers for A/T/N Classification of Alzheimer Disease Among Adults of Caribbean Hispanic Ethnicity.
Lawrence S Honig et al. JAMA Netw Open (4) e238214

Can plasma biomarker analytes be used in a low-resource community to improve clinical accuracy in diagnosing Alzheimer disease (AD)? In this decision analytical modeling study of 746 Caribbean Hispanic individuals from the Dominican Republic and New York, a panel of plasma biomarkers, including phosphorylated tau181 (P-tau181) and the ratio of P-tau181 to amyloid-ß Aß42, identified biological evidence of AD. A proportion of asymptomatic individuals without dementia had biomarker evidence of AD and may be presymptomatic, while a proportion of affected individuals with dementia lacked biomarker evidence of AD and may have other dementia disorders.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.
Xiaopu Zhou et al. Communications medicine 2023 4 (1) 49

The polygenic nature of Alzheimer’s disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual’s genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms.

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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