Measurement of lactate levels in postmortem brain, iPSCs, and animal models of schizophrenia

Sullivan, Courtney R.; Mielnik, Catharine A.; Funk, Adam; O’Donovan, Sinead M.; Bentea, Eduard; Pletnikov, Mikhail V.; Ramsey, Amy J.; Wen, Zhexing; Rowland, Laura M.; McCullumsmith, Robert E.

doi:10.1038/s41598-019-41572-9

Cited by 54 publications

(46 citation statements)

References 41 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, postmortem samples from SCZ patients show an increase in lactate metabolism [29,33]. Interestingly, we also observed high persistence in metabolic processes, which further supports this concept of metabolic compensation for a loss of oxidative phosphorylation in SCZ.…”

Section: Discussionsupporting

confidence: 84%

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Smail

Reigle

McCullumsmith

2020

Preprint

Self Cite

View full text Add to dashboard Cite

ABSTRACTOne of the major issues with RNA sequencing is the lack of reproducibility between RNA and protein expression. Transcriptomics offers a holistic view of the molecular landscape of a tissue at an RNA level. However, RNA and protein expression are often at odds when measured in the same sample, raising the question whether or not changes in RNA expression translate to functional differences. This problem creates a need to devise a way to approximate protein abundance from transcriptomics data, in order to create a more complete picture of the functional landscape of a tissue. One additional measure that could be useful here is protein turnover or half-life. Once RNA is transcribed into protein, that protein can either be quickly degraded or remain in the cell for an extended period of time. The longer a protein’s half-life, the more influence it can have on its surroundings. Recently, a study used stable isotope labeling in mammals (SILAM) in combination with mass spectrometry to determine the turnover ratio of ∼2200 protein in mouse synaptosomes. This data offers a valuable opportunity to integrate protein turnover with RNA expression to gain deeper insight into the functional meaning of RNA expression changes. Here, we present the concept of this combination of protein turnover and RNA expression, which we coined as persistence. We then demonstrate the application of persistence using schizophrenia (SCZ) transcriptomics datasets. Calculating persistence for these datasets greatly improved our ability to predict protein expression from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight that can be gained from transcriptomics data.

show abstract

Section: Discussionsupporting

confidence: 84%

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Smail

Reigle

McCullumsmith

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…[ 97 ] Frontal cortical neurons derived from iPSCs from an SCZ subject with DISC1 mutation showed similar bioenergetic dysfunction. [ 98 ] Compromised mitochondrial function was also reported in SCZ iPSC‐derived cortical interneurons, which was reversed by treatment with the alpha‐lipoic acid/acetyl‐ l ‐carnitine (ALA/ALC). [ 99 ]…”

Section: Mitochondria Dysfunction In People With Schizophreniamentioning

confidence: 99%

Mitochondrial Dysfunction in Schizophrenia

Chung

2020

BioEssays

View full text Add to dashboard Cite

Schizophrenia (SCZ) is a severe neurodevelopmental disorder affecting 1% of populations worldwide with a grave disability and socioeconomic burden. Current antipsychotic medications are effective treatments for positive symptoms, but poorly address negative symptoms and cognitive symptoms, warranting the development of better treatment options. Further understanding of SCZ pathogenesis is critical in these endeavors. Accumulating evidence has pointed to the role of mitochondria and metabolic dysregulation in SCZ pathogenesis. This review critically summarizes recent studies associating a compromised mitochondrial function with people with SCZ, including postmortem studies, imaging studies, genetic studies, and induced pluripotent stem cell studies. This review also discusses animal models with mitochondrial dysfunction resulting in SCZ-relevant neurobehavioral abnormalities, as well as restoration of mitochondrial function as potential therapeutic targets. Further understanding of mitochondrial dysfunction in SCZ may open the door to develop novel therapeutic strategies that can address the symptoms that cannot be adequately addressed by current antipsychotics alone.

show abstract

“…This again indicates that there is a loss of efficiency in SCZ that puts more stress on the system and forces neurons to turn to alternate sources of energy. Indeed, postmortem samples from SCZ patients show an increase in lactate metabolism 29 , 33 . Interestingly, we also observed high persistence in metabolic processes, which further supports this concept of metabolic compensation for a loss of oxidative phosphorylation in SCZ.…”

Section: Discussionmentioning

confidence: 99%

Using protein turnover to expand the applications of transcriptomics

Smail

Reigle

McCullumsmith

2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

RNA expression and protein abundance are often at odds when measured in parallel, raising questions about the functional implications of transcriptomics data. Here, we present the concept of persistence, which attempts to address this challenge by combining protein half-life data with RNA expression into a single metric that approximates protein abundance. The longer a protein’s half-life, the more influence it can have on its surroundings. This data offers a valuable opportunity to gain deeper insight into the functional meaning of transcriptome changes. We demonstrate the application of persistence using schizophrenia (SCZ) datasets, where it greatly improved our ability to predict protein abundance from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight offered by transcriptomics data, and extended application of this concept could advance numerous research fields.

show abstract

Measurement of lactate levels in postmortem brain, iPSCs, and animal models of schizophrenia

Cited by 54 publications

References 41 publications

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Mitochondrial Dysfunction in Schizophrenia

Using protein turnover to expand the applications of transcriptomics

Contact Info

Product

Resources

About