Dataset Information

Integrative multi-omics analysis to characterize human brain ischemia

ABSTRACT: 1. Rationale: Stroke is still a major cause of death and disability worldwide. A better comprehension of stroke pathophysiology is fundamental to reduce its dramatic outcome. The use of high-throughput unbiased omics approaches, such as proteomics and transcriptomics, might aid to deepen the knowledge of stroke at the molecular level. Moreover, the integration of omics data is needed to depict the existing interaction between different molecular units and interpret the results in a global biological context. 2. Objective: Our aim was to identify and verify protein and gene expression changes that occur in the human brain after ischemia through an integrative approach to join and combine the information of both omics analyses. The translational potential of our results was explored in a pilot study with blood samples from ischemic stroke patients. 3. Methods and results: Proteomics and transcriptomics discovery studies were performed in human brain samples from deceased stroke patients, unveiling 128 proteins and 2716 genes significantly dysregulated after cerebral ischemia. Afterwards, integrative bioinformatics analyses joining both datasets exposed several canonical pathways altered in the ischemic area, such as neurotransmitters release or matrisome regulation, highlighting the most influential molecules in these pathways. To conduct the verification phase, 28 genes and 9 proteins were selected to be validated in independent human brain samples by means of orthogonal techniques. Our results were confirmed for NCDN, RAB3C, ST4A1, DNM1L, A1AG1, A1AT, JAM3, VTDB, ANXA1, ANXA2 and IL8. Finally, the blood circulating levels of the validated protein candidates were explored in ischemic stroke patients over the acute phase of the disease. Protein fluctuations along the first week after onset were detected for A1AG1 and A1AT. 4. Conclusion: The results presented here expand the knowledge of stroke pathology, revealing new key molecules that can be further explored as biomarkers and/or therapeutic targets of ischemic stroke.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Brain

SUBMITTER: Laura Ramiro

LAB HEAD: Joan Montaner

PROVIDER: PXD022850 | Pride | 2022-12-21

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	2014_04_29_OT_PAA_100_VIL_JCS_N22_3_GPF1.raw	Raw
	2014_04_29_OT_PAA_101_VIL_JCS_N22_3_GPF2.raw	Raw
	2014_04_29_OT_PAA_102_VIL_JCS_N22_3_GPF3.raw	Raw
	2014_04_29_OT_PAA_103_VIL_JCS_N22_3_GPF4.raw	Raw
	2014_04_29_OT_PAA_112_VIL_JCS_N32_5_GPF1.raw	Raw

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Publications

Integrative Multi-omics Analysis to Characterize Human Brain Ischemia.

Ramiro Laura L García-Berrocoso Teresa T Briansó Ferran F Goicoechea Leire L Simats Alba A Llombart Víctor V Gonzalo Ricardo R Hainard Alexandre A Martínez-Saez Elena E Canals Francesc F Sanchez Jean-Charles JC Sánchez-Pla Alex A Montaner Joan J

Molecular neurobiology 20210503 8

Stroke is a major cause of death and disability. A better comprehension of stroke pathophysiology is fundamental to reduce its dramatic outcome. The use of high-throughput unbiased omics approaches and the integration of these data might deepen the knowledge of stroke at the molecular level, depicting the interaction between different molecular units. We aimed to identify protein and gene expression changes in the human brain after ischemia through an integrative approach to join the information ...[more]

PMID: 33939164

Similar Datasets

Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput - omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling network-like correlation structures, we identified a set of differentially expressed genes and proteins by ischemia with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice, and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted and evaluated as potential blood biomarkers of cerebral ischemia in blood samples from ischemic and sham-control mice and from ischemic strokes and other patients presenting stroke-mimicking conditions. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology, highlighting new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.

Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput -omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling net-like correlation structures, we identified a set of differentially expressed genes and proteins with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted as potential candidates as blood biomarkers of cerebral ischemia and hence they were evaluated in blood samples from ischemic and sham-control mice and in ischemic strokes and patients presenting stroke-mimicking conditions. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach that enabled us to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology and highlight new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.