Biomarkers.

Background: Two main risk factors of Alzheimer's disease (AD) are aging and APOE-ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered "cognitively resilient".

Developing Topics.

Background: Alzheimer's disease (AD) is a devastating form of dementia, and its prevalence is rising as human lifespan increases. Our lab created the AD-BXD mouse model, which expresses AD mutations across a genetically diverse reference panel (BXD), to identify factors that confer resilience to cognitive decline in AD. This model mimics key characteristics of human AD including variation in age of onset and severity of cognitive decline.

Developing Topics.

Background: Sleep dysfunctions are highly comorbid with Alzheimer's disease (AD), though often associated with later stages of AD, sleep disruptions have been noted to appear decades before the onset of cognitive symptoms. Here, we provide the first evidence that genetic factors interact with AD mutations to influence sleep behavior even before the onset of cognitive symptoms.

Method: To identify novel genetic factors underlying disordered sleep that precede cognitive decline in our AD-BXD mouse genetic reference panel (n = 179 mice across 25 strains, 7-months-old), we first used sleep phenotypes measured in the PiezoSleep chambers and performed quantitative trait loci (QTL) mapping and discovered Kirrel3 as the novel gene candidate associated with disordered sleep.

Strontium isoscape of sub-Saharan Africa allows tracing origins of victims of the transatlantic slave trade.

Strontium isotope (Sr/Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving Sr/Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the Sr/Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression.