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. 2024 Jul 12;11(1):768.
doi: 10.1038/s41597-024-03485-9.

Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

Maria Victoria Fernandez  1   2   3 , Menghan Liu  1   2 , Aleksandra Beric  1   2 , Matt Johnson  1   2 , Arda Cetin  1   2 , Maulik Patel  1   2 , John Budde  1   2 , Pat Kohlfeld  1   2 , Kristy Bergmann  1   2 , Joseph Lowery  1   2 , Allison Flynn  1   2 , William Brock  1   2 , Brenda Sanchez Montejo  1   2 , Jen Gentsch  1   2 , Nicholas Sykora  1   2 , Joanne Norton  1   2 , Jen Gentsch  1   2 , Olga Valdez  1   2 , Priyanka Gorijala  1   2 , Jessie Sanford  1   2 , Yichen Sun  1   2 , Ciyang Wang  1   2 , Dan Western  1   2 , Jigyasha Timsina  1   2 , Tassia Mangetti Goncalves  4 , Anh N Do  1   2   5 , Yun Ju Sung  1   2 , Guoyan Zhao  4   6   7 , John C Morris  6   8 , Krista Moulder  6   8 , David M Holtzman  6   8   9 , Randall J Bateman  6   8   9   10 , Celeste Karch  1   8   9   10 , Jason Hassenstab  6   8 , Chengjie Xiong  5   6   8   10 , Suzanne E Schindler  6   8 , Joyce Joy Balls-Berry  6   8 , Tammie L S Benzinger  6   8   10   11 , Richard J Perrin  7   8   10 , Andrea Denny  6   8 , B Joy Snider  6   8   9 , Susan L Stark  8   12 , Laura Ibanez  13   14   15   16 , Carlos Cruchaga  17   18   19   20   21   22   23
Affiliations

Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

Maria Victoria Fernandez et al. Sci Data. .

Abstract

The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.

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Conflict of interest statement

DMH has equity and is on the scientific advisory board of C2N Diagnostics. DMH is on the scientific advisory board of Denali, Genentech, and Cajal Neuroscience and consults for Asteroid. RB has received funding from NIH, Alzheimer’s Association, Biogen, AbbVie, Bristol Meyer Squibbs, Novartis, and EISAI. RB has equity and is on the scientific advisory board of C2N Diagnostics. SES has served on advisory boards and consulted on biomarker testing for Eisai, and she has received speaker fees from Eli Lilly. TLSB received research funding from Siemens and is an investigator on clinical trials and studies of AD with partial support from Eisai, Lilly, Roche, Janssen, and Biogen. TLSB is a consultant to Eisai. CC has received research support from: GSK and Eisai. CC is a member of the advisory board of Circular Genomics and owns stocks. CC is a member of the advisory board of ADmit.

Figures

Fig. 1
Fig. 1
Longitudinal blood DNA, RNA, and unfasted plasma samples stored at the GHTO (a). Stored samples at GHTO by number of assessments of each Knight-ADRC participant (b). Time between assessments with phlebotomy for Knight-ADRC participants with more than one visit. Blue represents DNA isolated from blood, yellow RNA extracted from blood, and dark pink for unfasted plasma.
Fig. 2
Fig. 2
Upset plots summarizing the -omic data layers generated by GHTO investigators and available to the scientific community. This representation does not contain longitudinal samples or brain regions, all graphs represent unique individuals with at least one data point (a). Summary of all the high-throughput data available for brain samples; (b). Distribution of the transcriptomic data by RNA tissue of origin; (c). Fasted CSF proteomic and metabolomic data available; (d). High-throughput protein measurements performed across tissues (brain, CSF, and plasma); (e). High-throughput data availability from whole blood (bulk transcriptomics) and plasma; and (f). Metabolomic data generated in brain, CSF, and plasma samples. Transcriptomic data is depicted with dark pink, proteomic data in yellow, metabolomic data in blue, and genomic data in green.
Fig. 3
Fig. 3
Genomic data available at the GHTO (a). Distribution of genomic data from Knight-ADRC individuals across technologies (b). Ancestry distribution of Knight-ADRC participants with genomic data available calculated using the first two principal components (c). Polygenic risk scores for AD, PD, and FTD distribution across knight-ADRC participants by diagnostic at last assessment. WES = Whole Exome Sequencing; WGS = Whole Genome Sequencing; GWAS = Genome Wide Association Study; AD = Alzheimer Disease; ADAD = Autosomal Dominant Alzheimer Disease; ADRD = Alzheimer Disease Related Dementia; DLB = Lewy Body Dementia; FTD = FrontoTemporal Dementia.
Fig. 4
Fig. 4
Two by two comparison of CSF soluble TREM2 levels measured using different technologies (a). CSF Soluble TREM2 levels correlation between high-throughput platform SomaScan and traditional ELISA (b). CSF soluble TREM2 measurement correlation between SomaScan and Alamar (NULISA) (c). Correlation between the measurements of soluble TREM2 in CSF using ELISA or Alamar technologies.
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