| Chapter title |
Unbiased Lipidomics and Metabolomics of Human Brain Samples
|
|---|---|
| Chapter number | 17 |
| Book title |
Biomarkers for Alzheimer’s Disease Drug Development
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7704-8_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7703-1, 978-1-4939-7704-8
|
| Authors |
Giuseppe Astarita, Matteo Stocchero, Giuseppe Paglia, Astarita, Giuseppe, Stocchero, Matteo, Paglia, Giuseppe |
| Abstract |
Mass spectrometry (MS)-based lipidomics and metabolomics approaches have been used to discover new diagnostic and therapeutic targets of neurodegenerative disorders. Here, we describe a protocol to conduct an integrated metabolomics and lipidomics profiling of postmortem brains of frozen tissue samples from clinically characterized patients and age-matched controls. Metabolites and lipids can be extracted from each brain tissue sample, using a biphasic liquid/liquid extraction method. An unbiased liquid chromatography MS-based lipidomics and metabolomics workflows allows to screen for the content and composition of lipids and polar metabolites for each brain tissue. Data processing and statistical analysis are then used to compare the molecular content of all the samples, grouping them into cluster based on molecular similarities. The final results highlight classes of metabolites and biochemical pathways that are altered in brain samples from diseased brains compared to those from healthy subjects, helping to generate novel hypotheses on their mechanistic and functional significance. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 27% |
| Student > Ph. D. Student | 3 | 20% |
| Other | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Professor | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 3 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 27% |
| Neuroscience | 4 | 27% |
| Psychology | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Chemistry | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 4 | 27% |