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- LysoPC(20:0) (2)
- MS neurodegeneration (2)
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- untargeted metabolomics (2)
Institute
The fall into the Oligocene icehouse is marked by a steady decline in global temperature with punctuated cooling at the Eocene-Oligocene transition, both of which are well documented in the marine realm. However, the chronology and mechanisms of cooling on land remain unclear. Here, we use clumped isotope thermometry on northeastern Tibetan continental carbonates to reconstruct a detailed Paleogene surface temperature record for the Asian continental interior, and correlate this to an enhanced pollen data set. Our results show two successive dramatic (>9 degrees C) temperature drops, at 37 Ma and at 33.5 Ma. These large-magnitude decreases in continental temperatures can only be explained by a combination of both regional cooling and shifts of the rainy season to cooler months, which we interpret to reflect a decline of monsoonal intensity. Our results suggest that the response of Asian surface temperatures and monsoonal rainfall to the steady decline of atmospheric CO2 and global temperature through the late Eocene was nonlinear and occurred in two steps separated by a period of climatic instability. Our results support the onset of the Antarctic Circumpolar Current coeval to the Oligocene isotope event 1 (Oi-1) glaciation at 33.5 Ma, reshaping the distribution of surface heat worldwide; however, the origin of the 37 Ma cooling event remains less clear.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.