Publications by authors named "J E Vance"

Background: Common and rare variants in SORL1 have been associated with increased risk of Alzheimer's disease (AD). Since 2019, we have run an international collaborative research initiative to ascertain a Peruvian cohort for Alzheimer's disease and other related dementias for genetic studies (PeADI).

Method: A Peruvian family (4 AD cases and two mild cognitive impairment (MCI) cases) was recruited through the PeADI study.

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Background: Alzheimer's disease (AD) missing heritability remains extensive despite numerous genetic risk loci identified by genome-wide association or sequencing studies. This has been attributed, at least partially, to mechanisms not currently investigated by traditional single-marker/gene approaches. Polygenic Risk Scores (PRS) aggregate sparse genetic information across the genome to identify individual genetic risk profiles for disease prediction and patient risk stratification.

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Background: Annotation of target genes of non-coding GWAS loci remains a challenge since 1) regulatory elements identified by GWAS can be metabases away from its actual target, 2) one regulatory element can target multiple genes, and 3) multiple regulatory elements can target one gene. AD GWAS in populations with different ancestries have identified different loci, suggesting ancestry-specific genetic risks. To understand the connection between associated loci (potential regulatory elements) and their target genes, we conducted Hi-C analysis in frontal cortex of African American (AA) and Non-Hispanic Whites (NHW) AD patients to map chromatin loops, which often represent enhancer-promoter (EP) interactions.

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Background: Prior studies have shown differences in the genetic etiology and clinical presentation of Alzheimer's Disease across populations. For example, for multiple genetic loci associated with AD, effect sizes can vary drastically between individuals of different ancestral backgrounds. Few investigations into differences in epigenetic features like DNA methylation have been conducted in AD, particularly in diverse individuals.

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Background: Polygenic Risk Scores (PRS) are important in predicting disease risk and are usually rely on markers selected by thresholding p-values from genome-wide association studies (GWAS). In traditional approaches, one single model is built to calculate risk scores, employing effect size to determine additive risk. However, this traditional method overlooks potential interactions between genetic loci resulting in reduced prediction power.

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