Clish, Clary B.

AbstractBackgroundAPOE ε4 is the strongest genetic risk factor for late‐onset Alzheimer’s disease (AD). The contribution of microglial APOE4 to AD pathogenesis is unknown, although APOE has the most enriched gene expression in neurodegenerative microglia (MGnD).MethodGeneration of CX3CR1‐CREERT2 mice crossed to APOE‐KI(E3 and E4)fl/fl: APP/PS1 and APOE‐KI(E3 and E4)fl/fl: P301S mice. Microglia and astrocytes were isolated and sequenced using either bulk RNA‐seq (MGnD‐Paradigm) or single‐cell RNA‐seq. Crosstalk between cells was determined using the NichenetR database and validated using 1) recombinant Lgals3 intracranial injection into APP/PS1 mice and 2) adoptive transfer of microglia, from APOE3‐KI, APOE4‐KI, and APOE4‐cKO mice challenged with labeled apoptotic neurons, into WT mice and isolation of astrocytes. Validation in the brain of AD donors carrying the APOE e3/3 and e3/4 alleles.ResultHere we show, in mice and in humans, a negative role of microglial APOE4 in the induction of MGnD response to neurodegeneration. Deletion of microglial APOE4 restores MGnD phenotype, associated with neuroprotection in P301S tau transgenic mice, and decreases pathology in APP/PS1 mice. MGnD‐astrocyte crosstalk associated with b‐amyloid (Ab) plaque encapsulation and clearance is mediated via Lgals3 signaling following microglial APOE4 deletion. In the brain of AD donors carrying the APOE ε4 allele, we found a sex‐dependent reciprocal induction of AD risk factors associated with suppression of MGnD genes in females, including LGALS3, as compared to APOE ε3/3 carriers. Mechanistically, APOE4‐mediated induction of ITGB8‐TGFb signaling impairs MGnD response via upregulation of TGFb‐mediated microglial homeostatic checkpoints, including INPP5D. Microglial deletion of Inpp5d restores MGnD‐astrocyte crosstalk and facilitates plaque clearance in APP/PS1 mice. Genetic and pharmacological blocking of ITGB8‐TGFb signaling enhanced MGnD response associated with increased plaque clearance in AD mice.ConclusionWe identify the microglial APOE4‐ITGB8‐TGFb pathway as a negative regulator of microglia‐astrocyte response to AD pathology, and restoring MGnD phenotype via blocking ITGB8‐TGFb signaling may provide new molecular targets to modulate and restore functional microglia in AD.

Abstract In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. We identified metabolites associated with higher or lower risk of HF incidence, the associations that were not confounded by the other metabolites, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. We revealed the underlying relationships of the findings. For example, asparagine directly influenced glycine, and both were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids which are not synthesized in the human body and come directly from the diet. Metabolites may play a critical role in linking genetic background and lifestyle factors to HF progression. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates a mechanistic understanding of HF progression.

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to match proteomes to genomes for 2,812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We were able to correctly match 90%-95% of proteomes to their correct genome and for 95%-99% we could match the proteome to the 1% most likely genome. The accuracy of matching in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. When serial proteomes are available, the matching algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1,000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Abstract Background: Pancreatic cancer is associated with development of cachexia, a wasting syndrome thought to limit survival. Few studies have longitudinally quantified peripheral tissues or identified biomarkers predictive of future tissue wasting. Methods: Adipose and muscle tissue were measured by computed tomography (CT) at diagnosis and 50 to 120 days later in 164 patients with advanced pancreatic cancer. Tissue changes and survival were evaluated by Cox proportional hazards regression. Baseline levels of circulating markers were examined in relation to future tissue wasting. Results: Compared with patients in the bottom quartile of muscle change per 30 days (average gain of 0.8 ± 2.0 cm2), those in the top quartile (average loss of 12.9 ± 4.9 cm2) had a hazard ratio (HR) for death of 2.01 [95% confidence interval (CI), 1.12–3.62]. Patients in the top quartile of muscle attenuation change (average decrease of 4.9 ± 2.4 Hounsfield units) had an HR of 2.19 (95% CI, 1.18–4.04) compared with those in the bottom quartile (average increase of 2.4 ± 1.6 Hounsfield units). Changes in adipose tissue were not associated with survival. Higher plasma branched chain amino acids (BCAA; P = 0.004) and lower monocyte chemoattractant protein-1 (MCP-1; P = 0.005) at diagnosis were associated with greater future muscle loss. Conclusions: In patients with advanced pancreatic cancer, muscle loss and decrease in muscle density in 2 to 4 months after diagnosis were associated with reduced survival. BCAAs and MCP-1 levels at diagnosis were associated with subsequent muscle loss. Impact: BCAAs and MCP-1 levels at diagnosis could identify a high-risk group for future tissue wasting.