Biochemistry and Pharmacology - Research Publications

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    Extracellular vesicular lipids as biomarkers for the diagnosis of Alzheimer’s disease
    Su, H ; Rustam, YH ; Masters, CL ; Makalic, E ; McLean, C ; Hill, AF ; Barnham, KJ ; Reid, GE ; Vella, LJ (Wiley, 2021-12-31)
    An increasing number of studies have revealed that dysregulated lipid homeostasis is associated with the pathological processes that lead to Alzheimer’s disease (AD). If changes in key lipid species could be detected in the periphery, it would advance our understanding of the disease and facilitate biomarker discovery. Global lipidomic profiling of sera/blood however has proved challenging with limited disease or tissue specificity. Small extracellular vesicles (EV) in the central nervous system, can pass the blood-brain barrier and enter the periphery, carrying a subset of lipids that could reflect lipid homeostasis in brain. This makes EVs uniquely suited for peripheral biomarker exploration.
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    CuII(atsm) inhibits ferroptosis: Implications for treatment of neurodegenerative disease
    Southon, A ; Szostak, K ; Acevedo, KM ; Dent, KA ; Volitakis, I ; Belaidi, AA ; Barnham, KJ ; Crouch, PJ ; Ayton, S ; Donnelly, PS ; Bush, A (WILEY, 2020-02)
    BACKGROUND AND PURPOSE: Diacetyl-bis(4-methyl-3-thiosemicarbazonato)copperII (CuII (atsm)) ameliorates neurodegeneration and delays disease progression in mouse models of amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD), yet the mechanism of action remains uncertain. Promising results were recently reported for separate Phase 1 studies in ALS patients and PD patients. Affected tissue in these disorders shares features of elevated Fe, low glutathione and increased lipid peroxidation consistent with ferroptosis, a novel form of regulated cell death. We therefore evaluated the ability of CuII (atsm) to inhibit ferroptosis. EXPERIMENTAL APPROACH: Ferroptosis was induced in neuronal cell models by inhibition of glutathione peroxidase-4 activity with RSL3 or by blocking cystine uptake with erastin. Cell viability and lipid peroxidation were assessed and the efficacy of CuII (atsm) was compared to the known antiferroptotic compound liproxstatin-1. KEY RESULTS: CuII (atsm) protected against lipid peroxidation and ferroptotic lethality in primary and immortalised neuronal cell models (EC50 : ≈130 nM, within an order of magnitude of liproxstatin-1). NiII (atsm) also prevented ferroptosis with similar potency, whereas ionic CuII did not. In cell-free systems, CuII (atsm) and NiII (atsm) inhibited FeII -induced lipid peroxidation, consistent with these compounds quenching lipid radicals. CONCLUSIONS AND IMPLICATIONS: The antiferroptotic activity of CuII (atsm) could therefore be the disease-modifying mechanism being tested in ALS and PD trials. With potency in vitro approaching that of liproxstatin-1, CuII (atsm) possesses favourable properties such as oral bioavailability and entry into the brain that make it an attractive investigational product for clinical trials of ferroptosis-related diseases.
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    Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture
    Zhang, Q ; Sidorenko, J ; Couvy-Duchesne, B ; Marioni, RE ; Wright, MJ ; Goate, AM ; Marcora, E ; Huang, K-L ; Porter, T ; Laws, SM ; Sachdev, PS ; Mather, KA ; Armstrong, NJ ; Thalamuthu, A ; Brodaty, H ; Yengo, L ; Yang, J ; Wray, NR ; McRae, AF ; Visscher, PM (NATURE RESEARCH, 2020-09-23)
    Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.