Richard J. Caselli

This study identifies genetic risk factors for FTLD-TDP subtypes using whole-genome sequencing and meta-analysis across multiple cohorts.

This paper develops and validates an integrated model combining MRI and blood-based biomarkers to predict brain amyloid PET positivity with high accuracy.

This paper introduces a federated model to integrate sMRI, GWAS, and transcriptomics data in Alzheimer's disease to identify genetic and transcriptomic influences on brain imaging measures.

This paper introduces FMFS, a framework for selecting hippocampal morphometry features linked to Aβ/tau pathology, showing it outperforms existing methods and identifies key subregions for biomarker development.

This paper develops a method to predict brain amyloid burden using MRI-based morphometry statistics and sparse coding, achieving high accuracy in ADNI and OASIS cohorts.

This study finds that severe hyposmia (reduced sense of smell) is a distinguishing feature between dementia with Lewy bodies and Alzheimer’s disease dementia, based on neuropathological confirmation.

This study compares cognitive decline rates in Alzheimer's disease with and without clinically undiagnosed Lewy body disease, finding faster decline in those with undiagnosed Lewy body disease.

The paper identifies 579 proteins associated with cognitive trajectory in aging using proteomic analysis of human prefrontal cortex, highlighting mitochondrial and synaptic processes linked to cognitive stability.

The paper shows that unbalanced sample sizes in genome-wide heterozygosity analyses can create spurious correlations with disease status, advocating for balanced sample sizes to improve reproducibility.