Minerva Foundation

The potential of proteomic aging clocks for obesity research, and the extent of nonlinearity in longitudinal associations between body weight and biological aging, remain underexplored. We investigated how BMI at ages 18 and ~60, as well as changes in BMI from age 18 to ~60, relate to downstream epigenetic and proteomic aging. We also examined nonlinearity and interactions in these associations. Analyses were conducted in 401 Finnish twins with up to nine self-reported or measured BMI values collected over 40 years. Olink proteomic and Illumina DNA methylation data were generated from blood drawn at the last BMI measurement. From these data, we derived four proteomic and five epigenetic age estimates and modeled BMI change over time using mixed-effects models. Generalized additive models were then applied to examine(1) nonlinear associations between BMI trajectories and biological aging, adjusting for chronological age, and (2) interactions of baseline BMI with BMI change and BMI at ~60 years. BMI at 18 and ~60 years old and changes in BMI were associated with increased biological aging for most aging estimates. We found statistical evidence of nonlinearity for about one-third of the significant associations, mostly observed for proteomic clocks. We further identified suggestive evidence for interactions between BMI at 18 years and BMI at ~60 years in explaining variability in two proteomic clocks (p = 0.07; p = 0.09). In conclusion, our study illustrates the potential of proteomic clocks in obesity research and highlights that assuming linearity in associations between BMI trajectories and biological aging is a critical oversight.

Abstract Background Glial fibrillary acidic protein (GFAP) has emerged as a potential biomarker for central nervous system injuries in various conditions. Cardiogenic shock (CS) causes systemic hypoperfusion often leading to mental disturbances, but it is not known if GFAP can be used to assess potential cerebral damage and prognosis in CS. Purpose To determine the prognostic value of GFAP as a biomarker in CS. Methods Baseline levels of plasma GFAP were measured from patients that were enrolled in the prospective, multicentre CardShock study conducted between 2010 and 2012. The primary outcome was 90-day all-cause mortality. Survival analyses were performed using the Kaplan-Meier method. The predictive power of the modified CardShock risk score (CSS) for 90-day mortality was assessed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve. Results Plasma samples from 117 patients were included in this study. Mean age was 67 (±12) years and 88 (75%) were men. Acute coronary syndrome (ACS) was the main aetiology of CS (85%). Confusion was detected in 79 (70%) patients at presentation. Twenty-eight (25%) patients had been resuscitated before inclusion. 90-day all-cause mortality of the overall cohort was 45%. Median plasma GFAP level at baseline was 460 ng/L (interquartile range (IQR) 272–697) for the study cohort. The cutoff value (465 ng/L) for GFAP at baseline was determined using the highest Youden index of the ROC analysis. Using the established cutoff value, we found that higher GFAP levels were associated with increased mortality (Figure 1). GFAP was moderately correlated with lactate at baseline with Spearman correlation coefficient (rs) 0.504 (p < 0.001). GFAP levels were higher in patients with confusion at presentation [median 473 ng/L, (IQR 317–778) vs. 342 ng/L, (IQR 194–636), p = 0.009] and in patients that had been resuscitated from cardiac arrest before inclusion [525 ng/L (IQR 376–909) vs. 395 ng/L (IQR 230–668), p = 0.024]. Adding GFAP level above 465 ng/L as a variable to the CSS slightly improved the model’s predictive power on 90-day all-cause mortality [AUC 0.81, (95% CI 0.73–0.89) vs. AUC 0.79, (95% CI 0.73–0.86)]. Conclusion Higher levels of GFAP at baseline are associated with 90-day all-cause mortality and demonstrate potential as a biomarker for risk stratification in patients experiencing cardiogenic shock.

Thirty-eight years of pediatric heart transplantation (pHTx) within the Scandiatransplant organization were analyzed to describe volume trends, regional prevalence, underlying etiologies, and outcomes following listing and pHTx. Children <18years listed for pHTx from January 1st 1986 to December 31st 2023 were identified in the Scandiatransplant registry. The cohort was split into groups based on the era of listing (ERA I; 1986-1998, ERA II; 1999-2011, and ERA III; 2012-2023). A total of 597 children were listed and 461 (77.2%) reached pHTx. The regional incidence of pHTx was 4.0 per 100,000 live births. All centers performed a median of <4 pHTx per year. 6.5% were transplanted at <1 year of age. Waiting list duration increased over time, withdrawal frequency remained stable, and listing mortality decreased from 22.8% in ERA I to 6.8% in ERA III. The distribution of listing and transplant diagnoses were not different between eras. ABO-incompatible transplants increased over time, from 1.0% in ERA I to 8.8% in ERA III, as did transplant from ventricular assist devices (6.6% in ERA I, 19.9% in ERA III). Post-transplant survival was 78.0% at 10years and 51.4% at 30years. Survival was worse in patients with an etiology of congenital heart disease compared with cardiomyopathies. Era of listing was a determinant of listing mortality but not of post-transplant survival. Numbers of pHTx in the Scandiatransplant region are low but have increased with time. There has been a significant decrease in waiting list mortality over time, whereas improvements in post-pHTx outcomes have been less evident, most likely due to excellent short-term outcomes for the first graft recipients in the region.

To investigate the potential progression rate of cerebral small vessel disease (CSVD) in brain MRI among neurologically asymptomatic middle-aged individuals with type 1 diabetes. A total of 172 individuals with type 1 diabetes were re-examined with brain MRI 7.5 years after their initial visit. Baseline predictors of changes in CSVD, particularly cerebral microbleeds (CMBs) and white matter hyperintensities (WMHs) were analyzed. The proportion of individuals with type 1 diabetes with CSVD increased from 36% to 70% (P < 0.001), CMBs increased from 17% to 33% (P < 0.001), and WMHs from 23% to 63% (P < 0.001) at follow-up. The increase in CMBs was associated with baseline systolic blood pressure, HbA1c, and preexisting CMBs. The increases in CSVD and WMHs were associated only with age. The prevalence of CSVD doubled over a 7.5-year period in middle-aged individuals with type 1 diabetes.

The search for habitable exoplanets has improved with every passing year. New methods and advanced instrumentation with higher precision help find more habitable exoplanets and refine existing parameters of highly likely habitable exoplanets. This paper presents the Statistical-likelihood Exo-Planetary Habitability Index (SEPHI) values for Kepler-504 b (of star Kepler-504), Kepler-315 b, and Kepler-315 c (both revolving around star Kepler-315).1,2,3 SEPHI is based on the geometric mean of the likelihood Gaussian estimation of four different comparison criteria with Earth as the only place we know harboring life: Telluricity, Atmosphere and Planet Gravity, Surface Liquid Water, and Magnetic Field.4,5,6 The seven physical characteristics of exoplanets have been used to calculate those four criteria: planetary mass, planetary radius, orbital period, stellar mass, stellar radius, and stellar effective temperature. This is a follow-up to previously calculated ESI values for the three exoplanets mentioned above, with Kepler-504 b and Kepler-315 b having a high ESI of 71.23% and 69.44%, respectively.7 It has been found that Kepler-504 b (with a host M-type star (small red dwarf)) has a SEPHI value of 0, Kepler-315 b (with a host G-type star) has a SEPHI value of 0, and Kepler-315 c (with a host G-type star) has a SEPHI value of 0. Thus, more than a combination of host star type, the orbital radius of exoplanet, and the final ESI to determine probable habitability, a further in-depth analysis through SEPHI can help us confirm its actual habitability for Earth-based life.

Ubiquitin specific protease-14 (USP14) is critical for controlling proteostasis disturbed in human disorders, including Parkinson's disease (PD). Here we investigated USP14 in the regulation of α-synuclein (α-syn) degradation via the proteasome and autophagy. α-Syn and pS129 α-syn were elevated in USP14 gene-deleted SH-SY5Y dopaminergic cells with decreased proteasome activity. However, autophagy and coordinated lysosomal expression and regulation pathways were elevated in USP14 lacking cells with higher levels of the transcription factor TFEB. There was an increase in reactive oxidative species (ROS) and elongated mitochondria in USP14 deficient cells and counteracting oxidative stress decreased α-syn levels. Phosphoproteomics revealed that USP14 is phosphorylated at residue S143 that reduces its binding to the proteasome. Re-expression of wild-type and phospho-mimetic S143D-USP14 mutant lowered ROS and α-syn levels in USP14 lacking cells. USP14 is a promising factor to consider in PD to target α-syn through its regulation of proteasomes and oxidative stress in dopaminergic neurons.

Introduction:While some studies have explored associations between weight change and blood proteins, most have been intervention-based, offering limited insight into proteomic associations with long-term weight gain. It remains unclear whether plasma proteins are related to BMI fluctuation over time. This study investigates associations of long-term BMI changes and fluctuations with over 1,000 plasma proteins involved in cardiometabolic and inflammation functions.Data and Methods:The study included 304 Finnish adult twins (117 men) born before 1958 from the Older Finnish Twin Cohort, with BMI data spanning five time points (1975, 1981, 1990, 2011, and 2012–2014). Proteomic data were derived from blood samples collected at the last BMI measurement. Linear mixed-effects models analyzed individual BMI trajectories, producing intercepts (baseline BMI) and slopes (BMI change rates). BMI fluctuation was calculated as the average squared deviation from expected BMI across time points. Associations between BMI changes/fluctuation and (i) 1,231 plasma proteins related to cardiometabolic and inflammatory functions and (ii) polygenic risk scores for BMI (PRSBMI), as well as interaction effects between PRSBMI and baseline BMI on protein-BMI relationships were studied. Within-pair analyses using monozygotic twins were conducted to account for shared confounding factors.Results:A total of 135 proteins were associated with changes in BMI over 40 years, while 17 proteins were linked to fluctuation in BMI: 12 associations (10 with BMI changes and 2 with fluctuation) remained significant in within-twin pair analyses. PRSBMI associated with BMI changes but not with fluctuations. PRSBMI-protein interactions explaining BMI changes or fluctuation was found, though a single interaction between the CD72 protein and baseline BMI was observed.Conclusion:This study highlights significant associations between plasma proteins and long-term BMI changes and fluctuations, with no evidence of PRSBMI-protein interactions influencing BMI trends. These findings underscore the substantial role of environmental factors in shaping proteome-BMI associations over adulthood.

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared with primary eQTL signals, nonprimary eQTL signals had lower effect sizes, lower minor allele frequencies and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTLs with genome-wide association study (GWAS) signals for 28 cardiometabolic traits identified 1,835 genes. Inclusion of nonprimary eQTL signals increased discovery of colocalized GWAS-eQTL signals by 46%. Furthermore, 21 genes with ≥2 colocalized GWAS-eQTL signals showed a mediating gene dosage effect on the GWAS trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.