Author

David Glenn Clark

Indiana University IndianapolisORCID 0000-0002-8882-9205Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Assay:proteomics· 2 Approach:statistical model· 2 Assay:GWAS summary statistics· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1

Frequent Co-Authors

Chiadi U. OnyikeiD· 3 shared David S. KnopmaniD· 3 shared Erik D. RobersoniD· 3 shared Lawrence S. HonigiD· 3 shared Adam FleisheriD· 2 shared Angela OliveriD· 2 shared Arthur W. TogaiD· 2 shared Beau M. AncesiD· 2 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersNeuroscience

Chiadi U. OnyikeORCID

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3 papers

Recent·Most cited

NeurosciencebioRxivPreprintAug 31, 2026

Cerebrospinal fluid YWHAG:NPTX2 ratio predicts clinical severity and future phenoconversion in frontotemporal lobar degeneration

Hamilton Se‐Hwee Oh, Joshua D. Downer, Connor D. Dietz…·Scott J. Russo

The paper identifies the CSF YWHAG:NPTX2 ratio as a biomarker for predicting clinical severity and phenoconversion in FTLD, showing strong correlation with disease progression and improved trial design potential.

DOI 10.64898/2026.08.22.746470

humanproteomics

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Genetic & Genomic MedicineAlzheimer s Research & TherapyPeer-reviewedFeb 27, 2024

Polygenic effects on the risk of Alzheimer's disease in the Japanese population

Masataka Kikuchi, Akinori Miyashita, Norikazu Hara…·Gary R. Conrad

This paper evaluates the polygenic risk score for Alzheimer's disease in Japanese individuals, showing its utility despite genetic differences from European populations.

19 citationstop 4%

humanGWAS summary statistics

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NeuroscienceScientific ReportsPeer-reviewedMar 10, 2019

A blood-based signature of cerebral spinal fluid Aβ1-42 status

Benjamin Goudey, Bowen John Fung, Christine Schieber…·Kyle B. Womack

This paper develops a blood-based machine learning model to predict cerebral spinal fluid Aβ1-42 levels, showing high accuracy in identifying Alzheimer's disease risk.

25 citations

humanproteomics

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