Justin B. Miller

The paper identifies individuals with extreme polygenic risk scores (PRS) for Alzheimer's disease (AD) and shows they have significantly elevated AD risk across multiple ancestries and APOE diplotypes.

The paper evaluates 1,752 polygenic risk score models for Alzheimer's disease and finds significant variability in results across methods and ancestries.

The paper identifies contextual biases in the SegmentNT model, showing how input sequence length and nucleotide position affect predictions and suggests ways to mitigate these biases.

The paper evaluates how long-read sequencing reduces dark genomic regions in the CHM13 reference genome compared to shorter-read references.

The paper shows that a synonymous variant in PILRA decreases mRNA and protein levels by disrupting a ramp sequence, providing a biological mechanism for its association with Alzheimer's disease.

This study investigates how behavioral traits and genetic markers relate to fentanyl intake escalation in rats, identifying gene networks and transcription factors associated with addiction-prone behaviors.

The paper uses long-read RNAseq to identify new RNA isoforms in Alzheimer's disease brain tissue and demonstrates their medical relevance.

The paper uses blood RNA levels and machine learning to predict Clinical Dementia Rating (CDR) groups, finding that combining nonsignificant probes improves classification accuracy.

The paper identifies rare genetic variants associated with exceptional longevity through pedigree analysis and genomic screening in Utah populations.

The paper fails to replicate previously reported epistatic interactions between TF and HFE variants and AD risk using a larger dataset, suggesting potential false positives or complex interactions.