Florey Department of Neuroscience and Mental Health - Research Publications

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    Effect of gene variants on opioid dose, pain and adverse effect outcomes in advanced cancer: an explorative study
    Wong, AK ; Klepstad, P ; Somogyi, AA ; Vogrin, S ; Le, B ; Philip, J ; Rubio, JP (FUTURE MEDICINE LTD, 2023-12)
    Aim: Associations between gene variants and opioid net effect are unclear. We conducted an exploratory pharmacogenetic analysis of 35 gene variants and opioid response in advanced cancer. Patients & methods: This multi-center prospective cohort study included clinical data, questionnaires (pain and adverse effects) and DNA (blood). Negative binomial regression and logistic regression were used. Results: Within 54 participants, eight statistically significant associations (p = 0.002-0.038) were observed between gene variants and opioid dose, pain scores or adverse effects, the majority being within the neuroimmune TLR4 pathway (IL1B [rs1143634], IL2 [rs2069762], IL6 [rs1800795], BDNF [rs6265]) and ARRB2 pathway (ARRB2 [rs3786047], DRD2 [rs6275]). Conclusion: Neuroimmune pathway genes may contribute to differences in opioid response in cancer and may be included in future similar studies.
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    Lower levels of soluble β-amyloid precursor protein, but not β-amyloid, in the frontal cortex in schizophrenia
    Dean, B ; Duce, J ; Li, Q-X ; Masters, CL ; Scarr, E (Elsevier, 2024-01)
    We identified a sub-group (25%) of people with schizophrenia (muscarinic receptor deficit schizophrenia (MRDS)) that are characterised because of markedly lower levels of cortical muscarinic M1 receptors (CHRM1) compared to most people with the disorder (non-MRDS). Notably, bioinformatic analyses of our cortical gene expression data shows a disturbance in the homeostasis of a biochemical pathway that regulates levels of CHRM1. A step in this pathway is the processing of β-amyloid precursor protein (APP) and therefore we postulated there would be altered levels of APP in the frontal cortex from people with MRDS. Here we measure levels of CHRM1 using [3H]pirenzepine binding, soluble APP (sAPP) using Western blotting and amyloid beta peptides (Aβ1-40 and Aβ1-42) using ELISA in the frontal cortex (Brodmann's area 6: BA 6; MRDS = 14, non-MRDS = 14, controls = 14). We confirmed the MRDS cohort in this study had the expected low levels of [3H]pirenzepine binding. In addition, we showed that people with schizophrenia, independent of their sub-group status, had lower levels of sAPP compared to controls but did not have altered levels of Aβ1-40 or Aβ1-42. In conclusion, whilst changes in sAPP are not restricted to MRDS our data could indicate a role of APP, which is important in axonal and synaptic pruning, in the molecular pathology of the syndrome of schizophrenia.
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    Neuronal Replenishment via Hydrogel-Rationed Delivery of Reprogramming Factors
    Mahmoudi, N ; Wang, Y ; Moriarty, N ; Ahmed, NY ; Dehorter, N ; Lisowski, L ; Harvey, AR ; Parish, CL ; Williams, RJ ; Nisbet, DR (American Chemical Society, 2024-01-14)
    The central nervous system's limited capacity for regeneration often leads to permanent neuronal loss following injury. Reprogramming resident reactive astrocytes into induced neurons at the site of injury is a promising strategy for neural repair, but challenges persist in stabilizing and accurately targeting viral vectors for transgene expression. In this study, we employed a bioinspired self-assembling peptide (SAP) hydrogel for the precise and controlled release of a hybrid adeno-associated virus (AAV) vector, AAVDJ, carrying the NeuroD1 neural reprogramming transgene. This method effectively mitigates the issues of high viral dosage at the target site, off-target delivery, and immunogenic reactions, enhancing the vector's targeting and reprogramming efficiency. In vitro, this vector successfully induced neuron formation, as confirmed by morphological, histochemical, and electrophysiological analyses. In vivo, SAP-mediated delivery of AAVDJ-NeuroD1 facilitated the trans-differentiation of reactive host astrocytes into induced neurons, concurrently reducing glial scarring. Our findings introduce a safe and effective method for treating central nervous system injuries, marking a significant advancement in regenerative neuroscience.
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    Orphan peptide and G protein-coupled receptor signalling in alcohol use disorder
    Anversa, RG ; Maddern, XJ ; Lawrence, AJ ; Walker, LC (WILEY, 2024-03)
    Neuropeptides and G protein-coupled receptors (GPCRs) have long been, and continue to be, one of the most popular target classes for drug discovery in CNS disorders, including alcohol use disorder (AUD). Yet, orphaned neuropeptide systems and receptors (oGPCR), which have no known cognate receptor or ligand, remain understudied in drug discovery and development. Orphan neuropeptides and oGPCRs are abundantly expressed within the brain and represent an unprecedented opportunity to address brain function and may hold potential as novel treatments for disease. Here, we describe the current literature regarding orphaned neuropeptides and oGPCRs implicated in AUD. Specifically, in this review, we focus on the orphaned neuropeptide cocaine- and amphetamine-regulated transcript (CART), and several oGPCRs that have been directly implicated in AUD (GPR6, GPR26, GPR88, GPR139, GPR158) and discuss their potential and pitfalls as novel treatments, and progress in identifying their cognate receptors or ligands.
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    BRINGING THE BENCH TO THE BEDSIDE: UPDATES ON THE MIND STUDY AND WHAT A ROUTINELY AVAILABLE SIMPLE BLOOD TEST FOR NEUROFILAMENT LIGHT WOULD MEAN AT THE CLINICAL COAL FACE FOR PATIENTS AND FAMILIES, PSYCHIATRISTS, NEUROLOGISTS, GERIATRICIANS AND GENERAL PRACTITIONERS
    Eratne, D ; Lewis, C ; Cadwallader, C ; Kang, M ; Keem, M ; Santillo, A ; Li, QX ; Stehmann, C ; Loi, SM ; Walterfang, M ; Watson, R ; Yassi, N ; Blennow, K ; Zetterberg, H ; Janelidze, S ; Hansson, O ; Berry-Kravitz, E ; Brodtmann, A ; Darby, D ; Walker, A ; Dean, O ; Masters, CL ; Collins, S ; Berkovic, SF ; Velakoulis, D (SAGE PUBLICATIONS LTD, 2022-05)
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    Differential associations of modifiable and non‐modifiable dementia risk factors with memory decline and hippocampal volume loss in Aβ‐ and Aβ+ cognitively normal older adults
    Rosenich, E ; Pase, MP ; Yassi, N ; Fripp, J ; Laws, SM ; Fowler, CJ ; Rowe, CC ; Masters, CL ; Maruff, PT ; Lim, YY ; Group, AIBLR (Wiley, 2021-12)
    Abstract Background The extent to which modifiable and non‐modifiable risk factors contribute to cognitive decline in older people remains unclear. We sought to determine the association of modifiable and non‐modifiable components included in the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) score with memory decline and brain volume loss in cognitively normal (CN) older adults, taking Aβ status into account. Method AIBL study participants (age range: 60‐90) who completed ≥2 neuropsychological assessments and an Aβ PET scan (N=626) were included in this study. We computed the standard CAIDE (age, sex, APOE ε4 status, education, hypertension, body mass index, hypercholesterinemia, physical inactivity), and a modifiable CAIDE (modCAIDE; education, modifiable vascular risk factors) for each participant. Aβ+ was classified using a Centiloid ≥25. Linear mixed models assessed interactions between each CAIDE score on episodic memory (EM) and hippocampal volume (HV) over time in Aβ‐ and Aβ+ CNs. Non‐modifiable variables from the standard CAIDE (age, sex, ε4) were included as separate predictors in all modCAIDE models to assess differential associations. Result We observed a significant standard CAIDE x time interaction on EM decline in Aβ+ (β=‐0.08(0.04); p=0.02) and Aβ‐ participants (β=‐4.07(1.13); p<0.001), and a significant standard CAIDE x time interaction on HV loss in Aβ+ participants only (β=‐0.06(0.02); p=0.003). When modifiable and non‐modifiable CAIDE components were considered separately, we observed a significant ε4 x time interaction only for EM decline (β=‐0.32(0.07); p<0.001) and HV loss (β=‐0.13(0.04); p<0.001) in Aβ+ participants, but no significant modCAIDE x time interaction (both p’s>0.29). In Aβ‐ participants, we observed a significant modCAIDE x time interaction on memory decline (β=‐0.04(0.02); p=0.02), but no significant ε4 x time interaction (β=‐0.07(0.04); p=0.11). No significant ε4 x time or modCAIDE x time interactions were observed for HV loss in Aβ‐ participants. Conclusion Our results are consistent with previous studies showing that ε4 is associated with an increased rate of EM decline and HV loss in Aβ+ CNs. In Aβ‐ CNs, lower prevalence of modifiable cardiovascular risk factors was associated with better EM performance over time, suggesting interventions to reduce modifiable risk factors could be beneficial in this group.
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    Monthly computerized at‐home assessments to detect cognitive change in preclinical Alzheimer’s disease
    Jutten, RJ ; Amariglio, RE ; Properzi, MJ ; Buckley, RF ; Maruff, PT ; Stark, CE ; Yassa, MA ; Johnson, KA ; Sperling, RA ; Rentz, DM ; Papp, KV (Wiley, 2021-12)
    Abstract Background Alongside the increased focus on detecting Alzheimer’s disease (AD) pathology in the preclinical stage, there is a need to more rapidly track AD‐related cognitive changes that may emerge during this stage. Computerized cognitive testing has the potential to achieve this by enabling more frequent, remote, unsupervised assessments. Here, we aimed to investigate whether monthly at‐home assessments of a modified version of the Behavioural Pattern Separation Task‐Object Version (BPSO) could detect cognitive change in cognitively unimpaired (CU) individuals with and without abnormal AD biomarkers. Method N=110 CU participants (age=77.1±4.9, 61% female, MMSE 29±1.3) from the Harvard Aging Brain Study completed the BPSO monthly at‐home on an iPad as part of the Cogstate C3 battery for up to one year (6.3±3.9 months follow‐up). All participants underwent PIB‐PET imaging (1.25±1.05 years before at‐home baseline) and a subset (n=82) underwent Flortaucipir PET (0.56±0.4 years before at‐home baseline). Primary outcome of the BPSO is a metric reflecting the ability to correctly discriminate between stimuli that are similar but not identical to previously learned targets (score range 0‐1, higher scores reflecting better performance). Linear mixed models were used to characterize BPSO performance over months (including both linear and quadratic time terms to investigate nonlinear change), and to examine associations with amyloid (dichotomous) and medial‐temporal tau deposition (continuous) while adjusting for age, sex, education and their interactions with time. Result Overall, individuals’ BPSO performance improved over months, as shown by a significant quadratic effect of time (β=‐.002,p<.001) with a plateauing learning curve (Figure 1). On average, amyloid‐positive individuals (n=29) showed slightly worse BPSO performance (β=‐.06,p=.03) than amyloid‐negative individuals, but similar trajectories over time. However, the baseline amyloid effect was attenuated when limiting the sample to those with both amyloid and tau imaging. Less improvement over the year was associated with greater tau burden in the entorhinal cortex (Time*tau β=‐0.02,p=.019) (Figure 2). Conclusion We show that subtle alterations in pattern separation performance over repeated exposure in CU individuals are associated with tau deposition in the medial‐temporal lobe. This implies that unsupervised computerized testing using monthly learning paradigms may be an efficient way to early detect cognitive change associated with preclinical AD.
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    Association of neighborhood‐level socioeconomic advantage with cognition and dementia risk factors in an Australian cohort
    Cavuoto, MG ; Rowsthorn, E ; Lavale, A ; Yassi, N ; Maruff, PT ; Buckley, RF ; Lim, YY ; Pase, MP (Wiley, 2021-12)
    Abstract Background Residing in areas of low socioeconomic advantage is associated with increased risk of dementia1 and associated brain pathology2,3. Given the long and insidious course of dementia pathologies, it is critical to establish the effect of ‘exposomic’ risk factors in midlife and to understand which groups of people are particularly vulnerable. Therefore, the objective of this study was to examine whether cognitive performance or dementia risk factors differed according to neighborhood‐level socioeconomic advantage in cognitively normal middle‐aged people. Methods Our sample comprised 4798 participants from the Healthy Brain Project, an online cohort of community‐dwelling Australians aged 40‐70 years. Socioeconomic advantage was computed by matching participants’ residential address to the Australian Bureau of Statistics’ Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD), assigning each participant a decile score (10 being the most advantaged). Scores were related to dementia risk estimated using the CAIDE dementia risk score and cognitive performance measured with the Cogstate Brief Battery (CBB) in linear regression models. Results Of the 4798 participants (mean age±SD 56±7 years, 26% male), 2762 (58%) were classified as living within an area of high neighbourhood socioeconomic advantage (IRSAD scores ≥ 8th decile), 1296 resided in rural or regional areas (27%), and 984 identified as “non‐European” (21%). Each decile unit increase in neighborhood socioeconomic advantage was associated with a lower CAIDE dementia risk score (β±SE= ‐0.088±0.024, p <0.001), following adjustments for race and rurality, and with better memory performance (β±SE= 0.084±0.024, p <0.001), following adjustments for age, sex, race, education, and rurality. An interaction was observed with differences in memory performance between levels of neighborhood advantage (comparing scores above and below the 8th decile) being larger at older ages and in people with higher dementia risk scores (Figure 1). There was no association between neighborhood‐level advantage and attention. Conclusions In a middle‐aged Australian cohort, higher neighborhood‐level socioeconomic advantage was associated with superior memory and lower dementia risk scores. Efforts to lower dementia risk factors, particularly in relation to reducing the negative impacts of disadvantage, are needed to curtail the growing burden of dementia.
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    How lifestyle shapes the brain: Associations between physical activity, sleep, beta‐amyloid and cognitive function in older adults
    Sewell, KR ; Rainey‐Smith, SR ; Villemagne, VLL ; Peiffer, JJ ; Sohrabi, HR ; Taddei, K ; Ames, D ; Maruff, PT ; Laws, SM ; Masters, CL ; Rowe, CC ; Martins, RN ; Erickson, KI ; Brown, BM (Wiley, 2021-12)
    Abstract Background Lifestyle factors such as sleep and physical activity influence risk of cognitive decline and dementia. Higher habitual physical activity and optimal sleep are associated with better cognitive function and lower levels of Alzheimer’s disease biomarkers, including beta‐amyloid (Aß). There is currently a poor understanding of how physical activity may influence the relationship between sleep and cognition, and whether exercise and sleep interact to influence cognition and Aß. Developing this understanding is crucial for creating effective lifestyle interventions for dementia prevention. Method Data from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised to determine whether self‐reported physical activity moderates the cross‐sectional relationship between self‐reported sleep parameters (duration, efficiency, latency, disturbance, quality), cognitive function (episodic memory, attention and processing speed, executive function), and brain Aß (quantified by amyloid positron emission tomography, using the Centiloid scale). Analyses were adjusted for age, sex, APOE ε4 carriage, mood, premorbid intelligence, and collection point. Participants were 404 community‐dwelling cognitively normal older adults aged 60 and above (75.3 5.7 years). Data from a subset of participants (n = 220, aged 75.2 5.6 years) were used for analyses with AB as the outcome. Result Physical activity moderated the relationship between sleep duration and episodic memory (ß = ‐.09, SE = .03, p = .005), and sleep efficiency and episodic memory (ß = ‐.08, SE = .03, p = .016). Physical activity moderated the relationship between sleep duration and A® (ß = ‐.12, SE = .06, p = .036), and sleep quality and Aß (ß = .12, SE = .06, p = .029). Conclusion Physical activity may play an important role in the relationship between sleep and cognitive function, and sleep and brain Aß. Future longitudinal and intervention studies in this area are crucial for informing interventions for dementia prevention.