Circulating Cell Free DNA and DNA Double-Strand Breakage in Alzheimer's Disease.

Alzheimer's disease (AD) is an age-related neurodegenerative disease that is characterized by memory loss and multiple cognitive impairments. AD is pathologically characterized by age-dependent accumulation of amyloid-ß protein and the phosphorylation of tau protein in the brains of patients with AD. Clinically, manifestations of AD include cognitive decline, dementia, alterations of high-order brain functions, and movement disorders. Double-stranded DNA breaks are a lethal form of DNA damage and are typically repaired via non-homologous end joining and homologous recombination. However, in AD brain, repair mechanism is disrupted, leading to a cascade of events, cognitive dysfunction, organ failure and reduced lifespan. Increased circulating cell-free DNA in the blood, cerebrospinal fluid, and urine in patients with AD, can be used as early detectable biomarkers for AD. The purpose of our article is to explore the potential uses of cell-free DNA and double-stranded DNA breaks as prognostic markers for AD and examine the recent research on the application of these markers in studies.

Using electronic health record data to link families: an illustrative example using intergenerational patterns of obesity.

OBJECTIVE: Electronic health record (EHR) data are a valuable resource for population health research but lack critical information such as relationships between individuals. Emergency contacts in EHRs can be used to link family members, creating a population that is more representative of a community than traditional family cohorts. MATERIALS AND METHODS: We revised a published algorithm: relationship inference from the electronic health record (RIFTEHR). Our version, Pythonic RIFTEHR (P-RIFTEHR), identifies a patient's emergency contacts, matches them to existing patients (when available) using network graphs, checks for conflicts, and infers new relationships. P-RIFTEHR was run on December 15, 2021 in the Northwestern Medicine Electronic Data Warehouse (NMEDW) on approximately 2.95 million individuals and was validated using the existing link between children born at NM hospitals and their mothers. As proof-of-concept, we modeled the association between parent and child obesity using logistic regression. RESULTS: The P-RIFTEHR algorithm matched 1 157 454 individuals in 448 278 families. The median family size was 2, the largest was 32 persons, and 247 families spanned 4 generations or more. Validation of the mother-child pairs resulted in 95.1% sensitivity. Children were 2 times more likely to be obese if a parent is obese (OR: 2.30; 95% CI, 2.23-2.37). CONCLUSION: P-RIFTEHR can identify familiar relationships in a large, diverse population in an integrated health system. Estimates of parent-child inheritability of obesity using family structures identified by the algorithm were consistent with previously published estimates from traditional cohort studies.