Epistatic Features and Machine Learning Improve Alzheimer's Disease Risk Prediction Over Polygenic Risk Scores.

Background: Polygenic risk scores (PRS) are linear combinations of genetic markers weighted by effect size that are commonly used to predict disease risk. For complex heritable diseases such as late-onset Alzheimer's disease (LOAD), PRS models fail to capture much of the heritability. Additionally, PRS models are highly dependent on the population structure of the data on which effect sizes are assessed and have poor generalizability to new data.

Unearthing who and Y at Harewood Cemetery and inference of George Washington's Y-chromosomal haplotype.

An excavation conducted at Harewood Cemetery to identify the unmarked grave of Samuel Washington resulted in the discovery of burials presumably belonging to George Washington's paternal grandnephews and their mother, Lucy Payne. To confirm their identities this study examined Y-chromosomal, mitochondrial, and autosomal DNA from the burials and a living Washington descendant. The burial's Y-STR profile was compared to FamilyTreeDNA's database, which resulted in a one-step difference from the living descendant and an exact match to another Washington.

Investigative genetic genealogy for human remains identification.

Investigative genetic genealogy (IGG) has emerged as a highly effective tool for tying a forensic DNA sample to an identity. While much of the attention paid to IGG has focused on cases where the DNA is from an unknown suspect, IGG has also been used to help close hundreds of unidentified human remains (UHR) cases. Genome-wide single-nucleotide polymorphism (SNP) genotype data can be obtained from forensic samples using microarray genotyping or whole-genome sequencing (WGS) with protocols optimized for degraded DNA.

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores.

Background: Polygenic risk scores (PRS) are linear combinations of genetic markers weighted by effect size that are commonly used to predict disease risk. For complex heritable diseases such as late onset Alzheimer's disease (LOAD), PRS models fail to capture much of the heritability. Additionally, PRS models are highly dependent on the population structure of data on which effect sizes are assessed, and have poor generalizability to new data.

Northeastern Asian and Jomon-related genetic structure in the Three Kingdoms period of Gimhae, Korea.

The genetic history of prehistoric and protohistoric Korean populations is not well understood because only a small number of ancient genomes are available. Here, we report the first paleogenomic data from the Korean Three Kingdoms period, a crucial point in the cultural and historic formation of Korea. These data comprise eight shotgun-sequenced genomes from ancient Korea (0.

Extended kinship analysis of historical remains using SNP capture.

DNA-assisted identification of historical remains requires the genetic analysis of highly degraded DNA, along with a comparison to DNA from known relatives. This can be achieved by targeting single nucleotide polymorphisms (SNPs) using a hybridization capture and next-generation sequencing approach suitable for degraded skeletal samples. In the present study, two SNP capture panels were designed to target ~ 25,000 (25 K) and ~ 95,000 (95 K) nuclear SNPs, respectively, to enable distant kinship estimation (up to 4th degree relatives).

Genetic genealogy for cold case and active investigations.

Investigative genetic genealogy has rapidly emerged as a highly effective tool for using DNA to determine the identity of unknown individuals (unidentified remains or perpetrators), generating identifications in dozens of law enforcement cases, both cold and active. The amount of press coverage of these cases may have given the impression that the analysis is straightforward and the outcome guaranteed once a sample is uploaded to a database. However, the database query results serve only as clues from which in-depth genealogy and descendancy research must proceed to determine the possible identities of an unknown individual.

Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases.

Background: Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had some success, but much of the genetic architecture of common disease remains unexplained. Attention is now turning to detecting SNPs that impact disease susceptibility in the context of other genetic factors and environmental exposures.