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    Development of harmonized and co‐calibrated scores for memory, executive functioning, language, and visuospatial in the AIBL Study, ADNI, and NACC datasets
    Crane, PK ; Trittschuh, EH ; Mez, JB ; Saykin, AJ ; Sanders, RE ; Gibbons, LE ; Lee, ML ; Scollard, P ; Choi, S ; Rainey‐Smith, S ; Chooi, CK ; Gavett, BE ; Maruff, P ; Ames, D ; Culhane, JE ; Gauthreaux, K ; Chan, KCG ; Biber, S ; Stephens, K ; Kukull, WA ; Dumitrescu, L ; Hohman, TJ ; Mukherjee, S (Wiley, 2022-12)
    Background The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study is a prospective study collecting extensive cognitive, clinical, fluid, and imaging biomarkers data from older adults living in Australia. Integration of outcomes between large prospective studies of AD will provide greater precision in models of AD brain‐behavior relationships, so it is important to align composite scores for cognitive domains between such studies. Methods Detailed methods for AIBL, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the National Alzheimer’s Coordinating Center (NACC) have been published. Briefly, AIBL participants had cognition assessed with an extensive neuropsychological test battery alongside health and biomarker assessments at entry and each 18‐months thereafter. Granular‐level cognitive data were obtained and an expert panel of two neuropsychologists and a behavioral neurologist categorized each element as assessing memory, executive functioning, language, visuospatial, or none of these, exactly as we have done previously. We also identified elements we had previously calibrated from other studies; after careful quality control and confirmation these served as anchors enabling co‐calibration. We used confirmatory factor analysis bi‐factor models to calibrate the AIBL battery with other studies. We used those calibrations to obtain co‐calibrated scores for all AIBL participants at every study visit. Here we show descriptive statistics for baseline visits, separately by diagnosis (normal cognition, mild cognitive impairment (MCI), dementia) for two enrollment waves for AIBL as well as for each phase of ADNI and across the Uniform Data Set (UDS) 1 & 2 (UDS1/2) and UDS3 time periods for NACC. Results Box plots for memory, executive functioning, language, and visuospatial for people with normal cognition are in Figure 1, MCI in Figure 2, and dementia in Figure 3. These figures show there is substantial cognitive variation across waves within these disease stage groups and across studies. Conclusion Co‐calibrated neuropsychological domain scores provide a common metric for integrating cognitive data across studies. Co‐calibrated scores aggregated across large prospective AD studies such as AIBL, ADNI, and NACC provide a foundation for large‐scale models of the development of AD and can serve as phenotypes for genetics studies. Co‐calibrated scores are available from AIBL, ADNI, and from NACC.
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    Objectively measured physical activity and cognition in cognitively normal older adults: A longitudinal analysis of the Australian Imaging Biomarkers and Lifestyle (AIBL) study
    Sewell, KR ; Rainey‐Smith, S ; Villemagne, VL ; Peiffer, JJ ; Sohrabi, HR ; Taddei, K ; Ames, D ; Maruff, P ; Laws, SM ; Masters, CL ; Rowe, C ; Martins, RN ; Erickson, KI ; Brown, BM (Wiley Open Access, 2022-12)
    Background Physical inactivity is one of the greatest modifiable risk factors for dementia and research shows physical activity can delay cognitive decline in older adults. However, much of this research has used subjective physical activity data and a single follow‐up cognitive assessment. Further studies using objectively measured physical activity and comprehensive cognitive data measured at multiple timepoints are required. Methods Participants were 199 community‐dwelling cognitively normal older adults (68.7 5.9 years) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Actigraphy was used to measure physical activity at baseline, yielding measures of intensity (peak counts), total activity (total counts) and energy expenditure (kilocalories; k/cal). Cognitive function was assessed using a cognitive battery administered every 18‐months from baseline (3‐11 years follow‐up), yielding composite scores for episodic memory, executive function, attention and processing speed, and global cognition. Results Higher baseline energy expenditure predicted improvements in episodic memory and maintained global cognition over time (β = 0.011, SE = 0.005, p = 0.031; β = 0.009, SE = 0.004, p = 0.047, respectively). Both physical activity intensity and total activity predicted global cognition, such that those with higher peak and total counts had better cognition over time (β = 0.012, SE = 0.004, p = 0.005; β = 0.012, SE = 0.004, p = 0.005, respectively). Finally, higher total activity predicted improved episodic memory over time (β = 0.011, SE = 0.005, p = .022). Conclusion These results suggest that physical activity is associated with preserved cognitive function over time, and that activity intensity may play an important role. This research further highlights the importance of early intervention to prevent cognitive decline and may aid in informing lifestyle interventions for dementia prevention.
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    Plasma glial fibrillary acidic protein is associated with reactive astrogliosis assessed via 18F-SMBT-1 PET
    Chatterjee, P ; Dore, V ; Pedrini, S ; Krishnadas, N ; Thota, RN ; Bourgeat, P ; Rainey‐Smith, S ; Burnham, SC ; Fowler, C ; Taddei, K ; Mulligan, RS ; Ames, D ; Masters, CL ; Fripp, J ; Rowe, C ; Martins, RN ; Villemagne, VL (Wiley, 2022-12)
    Background Reactive astrogliosis is an early event along the Alzheimer’s disease (AD) continuum. We have shown that plasma glial fibrillary acidic protein (GFAP), reflecting reactive astrogliosis, is elevated in cognitively unimpaired individuals with preclinical AD (Chatterjee et al., 2021). We reported similar findings using 18F‐SMBT‐1, a PET tracer for monoamine oxidase B (MAO‐B) (Villemagne et al., 2022). To provide further evidence of their relationship with reactive astrogliosis we investigated the association between GFAP and 18F‐SMBT‐1 in the same participants. Method Plasma GFAP, Aβ42 and Aβ40 levels were measured using the Single Molecule Array platform in 71 participants comprising 54 healthy controls (12 Aβ+ and 42 Aβ‐), 11 MCI(3 Aβ+ and 8 Aβ‐) and 6 probable AD(5 Aβ+ and 1 Aβ‐) patients from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing cohort. These participants also underwent 18F‐SMBT‐1 and Aβ PET imaging. Aβ imaging results were expressed in Centiloids (CL; ≥20 CL classified as Aβ+). 18F‐SMBT‐1 Standard Uptake Value Ratio (SUVR) were generated using the subcortical white matter as reference region. Linear regression analyses were carried out using plasma GFAP levels as the dependent variable and regional 18F‐SMBT‐1 SUVR as the independent variable, before and after adjusting for age, sex, soluble Aβ (plasma Aβ1‐42/Aβ1‐40 ratio) and insoluble Aβ (Aβ PET). Result Plasma GFAP was significantly associated with 18F‐SMBT‐1 SUVR in brain regions of early Aβ deposition, such as the supramarginal gyrus (SG, β=.361, p=.002), posterior cingulate (PC, β=.308, p=.009), lateral temporal (LT, β=.299, p=.011), lateral occipital (LO, β=.313, p=.008) before adjusting for any covariates. After adjusting for covariates age, sex and soluble Aβ, GFAP was significantly associated with 18F‐SMBT‐1 PET signal in the SG (β=.333, p<.001), PC (β=.278, p=.005), LT (β=.256, p=.009), LO (β=.296, p=.004) and superior parietal (SP, β=.243, p=.016). On adjusting for age, sex and insoluble Aβ, GFAP was significantly associated with SMBT‐1 PET in the SG (β=.211, p=.037) however only a trend towards significance was observed in the PC (β=.186, p=.052) and LT (β=.171, p=.067) (Figure 1). Conclusion There is an association between plasma GFAP and regional SMBT‐1 PET that is primarily driven by brain Aβ load.
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    Lipidomic signatures for APOE genotypes provides new insights about mechanisms of resilience in Alzheimer’s disease
    Wang, T ; Huynh, K ; Giles, C ; Lim, WLF ; Duong, T ; Mellett, NA ; Smith, A ; Olshansky, G ; Drew, BG ; Cadby, G ; Melton, PE ; Hung, J ; Beilby, J ; Watts, GF ; Chatterjee, P ; Martins, I ; Laws, SM ; Bush, AI ; Rowe, CC ; Villemagne, VL ; Ames, D ; Masters, CL ; Arnold, M ; Kastenmüller, G ; Nho, K ; Saykin, AJ ; Baillie, R ; Han, X ; Martins, RN ; Moses, E ; Kaddurah‐Daouk, RF ; Meikle, PJ (Wiley, 2021-12)
    Background The apolipoprotein E gene (APOE) genotype is the first and strongest genetic risk factor for late‐onset Alzheimer’s disease and has emerged as a novel therapeutic target for AD. The encoded protein (Apolipoprotein E, APOE) is well‐known to be involved in lipoprotein transport and metabolism, but its effect on lipid metabolic pathways and the potential mediating effect of these on disease risk have not been fully defined. Method We performed lipidomic analysis on three independent cohorts (AIBL, n = 693; ADNI, n=207; BHS, n=4,384) and defined the association between APOE polymorphisms (ε4 and ε2) and plasma lipid species. To identify associations independent of lipoprotein metabolism, the analyses was performed with adjustment for clinical lipids (total cholesterol, HDL‐C and triglycerides). Causal mediation analysis was performed to estimate the proportion of risk in the outcome model explained by a direct effect of APOE genotype on prevalent AD — the average direct effect (ADE) — and the proportion that was mediated by lipid species or lipidomic risk models — the average causal mediation effect (ACME). Result We identified multiple associations of species from lipid classes such as ceramide, hexosylceramide, sphingomyelin, plasmalogens, alkyldiacylglycerol and cholesteryl esters with APOE polymorphisms (ε4 and ε2) that were independent of clinical lipoprotein measurements. There were 104 and 237 lipid species associated with APOE ε4 and ε2 respectively which were largely discordant. Of these 116 were also associated with Alzheimer’s disease. Individual lipid species (notably the alkyldiacylglycerol subspecies) or lipidomic risk models of APOE genotypes mediated up to 10% and 30% of APOE ε4 and ε2 treatment effect on AD risks respectively. Conclusion We demonstrate a strong relationship between APOE polymorphisms and peripheral lipid species. Lipids species mediate a proportion of the effects of APOE genotypes in risk of AD, particularly resilience with e2. Our results highlight the involvement of lipids in how APOE e2 mediates its resilience to AD and solidify their involvement with the disease pathway.
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    Higher coffee consumption is associated with slower cognitive decline and Aβ‐amyloid accumulation over 126 months: Data from the AIBL study
    Gardener, SL ; Rainey‐Smith, SR ; Villemagne, VLL ; Fripp, J ; Dore, V ; Bourgeat, P ; Taddei, K ; Masters, CL ; Maruff, PT ; Rowe, CC ; Ames, D ; Martins, RN (Wiley, 2021-12)
    Background Worldwide, coffee is one of the most popular beverages consumed. Several studies have suggested a protective role of coffee, including reduced risk of Alzheimer’s disease (AD). However, there is limited longitudinal data available in cohorts of older adults reporting associations of coffee intake with cognitive decline, in distinct domains, and investigating the neuropathological mechanisms underpinning these associations. Method The aim of the current study was to investigate the relationship between self‐reported baseline coffee intake (mean = 280 ± 323 g/day) and cognitive decline assessed using a comprehensive neuropsychological battery, over 126 months, in 227 cognitively normal individuals from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) study. We also sought to investigate the relationship between coffee intake and cerebral Aβ‐amyloid accumulation and brain volumes in a subset of individuals (n=60; and n=51, respectively) over 126 months. Result Higher baseline coffee consumption was associated with slower cognitive decline in executive function, attention, and the AIBL Preclinical AD Cognitive Composite (PACC; shown to reliably measure the first signs of cognitive decline in at‐risk cognitively normal populations) over 126 months. Higher baseline coffee consumption was also associated with slower Aβ‐amyloid accumulation over 126 months, and lower risk of transitioning from ‘negative’ Aβ‐amyloid status to ‘moderate’, and ‘very high’ Aβ‐amyloid burden over the same time period. There were no associations between coffee intake and atrophy in total grey matter, white matter, or hippocampal volume. Conclusion Our results further support the hypothesis that coffee intake may be a protective factor against AD, with increased coffee consumption reducing cognitive decline potentially by slowing cerebral Aβ‐amyloid accumulation, and thus attenuating the associated neurotoxicity from Aβ‐amyloid‐mediated oxidative stress and inflammatory processes. Further investigation is required to evaluate how coffee intake could be incorporated as one modifiable lifestyle factor aimed at delaying AD onset.
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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.
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    Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers
    Boen, R ; Kaufmann, T ; van der Meer, D ; Frei, O ; Agartz, I ; Ames, D ; Andersson, M ; Armstrong, NJ ; Artiges, E ; Atkins, JR ; Bauer, J ; Benedetti, F ; Boomsma, DI ; Brodaty, H ; Brosch, K ; Buckner, RL ; Cairns, MJ ; Calhoun, V ; Caspers, S ; Cichon, S ; Corvin, AP ; Crespo-Facorro, B ; Dannlowski, U ; David, FS ; de Geus, EJC ; de Zubicaray, GI ; Desrivieres, S ; Doherty, JL ; Donohoe, G ; Ehrlich, S ; Eising, E ; Espeseth, T ; Fisher, SE ; Forstner, AJ ; Fortaner-Uya, L ; Frouin, V ; Fukunaga, M ; Ge, T ; Glahn, DC ; Goltermann, J ; Grabe, HJ ; Green, MJ ; Groenewold, NA ; Grotegerd, D ; Grontvedt, GR ; Hahn, T ; Hashimoto, R ; Hehir-Kwa, JY ; Henskens, FA ; Holmes, AJ ; Haberg, AK ; Haavik, J ; Jacquemont, S ; Jansen, A ; Jockwitz, C ; Joensson, EG ; Kikuchi, M ; Kircher, T ; Kumar, K ; Le Hellard, S ; Leu, C ; Linden, DE ; Liu, J ; Loughnan, R ; Mather, KA ; Mcmahon, KL ; Mcrae, AF ; Medland, SE ; Meinert, S ; Moreau, CA ; Morris, DW ; Mowry, BJ ; Muehleisen, TW ; Nenadic, I ; Noethen, MM ; Nyberg, L ; Ophoff, RA ; Owen, MJ ; Pantelis, C ; Paolini, M ; Paus, T ; Pausova, Z ; Persson, K ; Quide, Y ; Marques, TR ; Sachdev, PS ; Sando, SB ; Schall, U ; Scott, RJ ; Selbaek, G ; Shumskaya, E ; Silva, AI ; Sisodiya, SM ; Stein, F ; Stein, DJ ; Straube, B ; Streit, F ; Strike, LT ; Teumer, A ; Teutenberg, L ; Thalamuthu, A ; Tooney, PA ; Tordesillas-Gutierrez, D ; Trollor, JN ; Van't Ent, D ; van den Bree, MBM ; van Haren, NEM ; Vazquez-Bourgon, J ; Voelzke, H ; Wen, W ; Wittfeld, K ; Ching, CRK ; Westlye, LT ; Thompson, PM ; Bearden, CE ; Selmer, KK ; Alnaes, D ; Andreassen, OA ; Sonderby, IE (ELSEVIER SCIENCE INC, 2024-01-15)
    BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
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    Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning
    Lahti, J ; Tuominen, S ; Yang, Q ; Pergola, G ; Ahmad, S ; Amin, N ; Armstrong, NJ ; Beiser, A ; Bey, K ; Bis, JC ; Boerwinkle, E ; Bressler, J ; Campbell, A ; Campbell, H ; Chen, Q ; Corley, J ; Cox, SR ; Davies, G ; De Jager, PL ; Derks, EM ; Faul, JD ; Fitzpatrick, AL ; Fohner, AE ; Ford, I ; Fornage, M ; Gerring, Z ; Grabe, HJ ; Grodstein, F ; Gudnason, V ; Simonsick, E ; Holliday, EG ; Joshi, PK ; Kajantie, E ; Kaprio, J ; Karell, P ; Kleineidam, L ; Knol, MJ ; Kochan, NA ; Kwok, JB ; Leber, M ; Lam, M ; Lee, T ; Li, S ; Loukola, A ; Luck, T ; Marioni, RE ; Mather, KA ; Medland, S ; Mirza, SS ; Nalls, MA ; Nho, K ; O'Donnell, A ; Oldmeadow, C ; Painter, J ; Pattie, A ; Reppermund, S ; Risacher, SL ; Rose, RJ ; Sadashivaiah, V ; Scholz, M ; Satizabal, CL ; Schofield, PW ; Schraut, KE ; Scott, RJ ; Simino, J ; Smith, AV ; Smith, JA ; Stott, DJ ; Surakka, I ; Teumer, A ; Thalamuthu, A ; Trompet, S ; Turner, ST ; van der Lee, SJ ; Villringer, A ; Voelker, U ; Wilson, RS ; Wittfeld, K ; Vuoksimaa, E ; Xia, R ; Yaffe, K ; Yu, L ; Zare, H ; Zhao, W ; Ames, D ; Attia, J ; Bennett, DA ; Brodaty, H ; Chasman, DI ; Goldman, AL ; Hayward, C ; Ikram, MA ; Jukema, JW ; Kardia, SLR ; Lencz, T ; Loeffler, M ; Mattay, VS ; Palotie, A ; Psaty, BM ; Ramirez, A ; Ridker, PM ; Riedel-Heller, SG ; Sachdev, PS ; Saykin, AJ ; Scherer, M ; Schofield, PR ; Sidney, S ; Starr, JM ; Trollor, J ; Ulrich, W ; Wagner, M ; Weir, DR ; Wilson, JF ; Wright, MJ ; Weinberger, DR ; Debette, S ; Eriksson, JG ; Mosley, TH ; Launer, LJ ; van Duijn, CM ; Deary, IJ ; Seshadri, S ; Raikkonen, K (SPRINGERNATURE, 2022-11)
    Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.
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    Genetic and environmental influences on fruit and vegetable consumption and depression in older adults
    Matison, APP ; Thalamuthu, A ; Flood, VMM ; Trollor, JNN ; Catts, VSS ; Wright, MJJ ; Ames, D ; Brodaty, H ; Sachdev, PSS ; Reppermund, S ; Mather, KAA (BMC, 2023-02-03)
    BACKGROUND: Prior work suggests that higher fruit and vegetable consumption may protect against depression in older adults. Better understanding of the influence of genetic and environmental factors on fruit and vegetable intakes may lead to the design of more effective dietary strategies to increase intakes. In turn this may reduce the occurrence of depression in older adults. OBJECTIVES: The primary aim of this study is to estimate the genetic and environmental influences on the consumption of fruit and vegetables in older adults. The secondary aim is an exploratory analysis into possible shared genetic influences on fruit and vegetable intakes and depression. METHODS: Analysis of observational data from 374 twins (67.1% female; 208 monozygotic (MZ); 166 dizygotic (DZ)) aged ≥ 65 years drawn from the Older Australian Twins Study. Dietary data were obtained using a validated food frequency questionnaire and depressive symptoms were measured using the 15-item short form Geriatric Depression Scale. The contribution of genetic and environmental influences on fruit and vegetable intake were estimated by comparing MZ and DZ twin intakes using structural equation modelling. A tri-variate twin model was used to estimate the genetic and environmental correlation between total fruit and vegetable intakes and depression. RESULTS: In this study, vegetable intake was moderately influenced by genetics (0.39 95%CI 0.22, 0.54). Heritability was highest for brassica vegetables (0.40 95%CI 0.24, 0.54). Overall fruit intake was not significantly heritable. No significant genetic correlations were detected between fruit and vegetable intake and depressive symptoms. CONCLUSIONS: Vegetable consumption, particularly bitter tasting brassica vegetables, was significantly influenced by genetics, although environmental influences were also apparent. Consumption of fruit was only influenced by the environment, with no genetic influence detected, suggesting strategies targeting the food environment may be particularly effective for encouraging fruit consumption.
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    High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile
    Revelas, M ; Thalamuthu, A ; Zettergren, A ; Oldmeadow, C ; Najar, J ; Seidu, NM ; Armstrong, NJ ; Riveros, C ; Kwok, JB ; Schofield, PR ; Trollor, JN ; Waern, M ; Wright, MJ ; Zetterberg, H ; Ames, D ; Belnnow, K ; Brodaty, H ; Scott, RJ ; Skoog, I ; Attia, JR ; Sachdev, PS ; Mather, KA (SPRINGER, 2023-02)
    Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10-42) and its components (p < 2.30 × 10-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity.