Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Generation and quality control of lipidomics data for the alzheimer's disease neuroimaging initiative cohort.

Authors: Dinesh Kumar, Barupal; Sili, Fan; Benjamin, Wancewicz; Tomas, Cajka; Michael, Sa; Megan R, Showalter; Rebecca, Baillie; +4 Authors

Generation and quality control of lipidomics data for the alzheimer's disease neuroimaging initiative cohort.

Abstract

Alzheimer's disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/.

Keywords

Aged, 80 and over, Cohort Studies, Alzheimer Disease, Humans, Metabolomics, Cognitive Dysfunction, Neuroimaging, Lipids, Mass Spectrometry, Aged

49 references, page 1 of 5

Sage Bionetworks. 2017

Sage Bionetworks. 2017

Sage Bionetworks. 2017

Sage Bionetworks. 2017

McKhann G.et al.Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34, 939–944 ( (1984).6610841 [OpenAIRE] [PubMed]

Montine T. J.et al.National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease: a practical approach. Acta Neuropathol.123, 1–11, ; DOI: 10.1007/s00401-011-0910-3 (2012).22101365 [OpenAIRE] [PubMed] [DOI]

Jack C. R.Jr.et al.Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol.12, 207–216 ; DOI: 10.1016/S1474-4422(12)70291-0 (2013).23332364 [OpenAIRE] [PubMed] [DOI]

Gotz J. & Ittner L. M. Animal models of Alzheimer’s disease and frontotemporal dementia. Nat Rev Neurosci 9, 532–544 ; DOI: 10.1038/nrn2420 (2008).18568014 [OpenAIRE] [PubMed] [DOI]

Toledo J. B.et al.Metabolic network failures in Alzheimer’s disease-A biochemical road map. Alzheimers Dement. ; DOI: 10.1016/j.jalz.2017.01.020 (2017). [OpenAIRE] [DOI]

Wong M. W.et al.Dysregulation of lipids in Alzheimer’s disease and their role as potential biomarkers. Alzheimers Dement.13, 810–827 ; DOI: 10.1016/j.jalz.2017.01.008 (2017).28242299 [OpenAIRE] [PubMed] [DOI]

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    46
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
46
Top 10%
Top 10%
Top 1%