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Diet has been investigated in relation to its ability to promote cognitive function. However, evidence is currently limited and has rarely been systematically reviewed, particularly in a mild cognitive impairment (MCI) population. This review examined the effect of diet on cognitive outcomes in MCI patients. A total of five databases were searched to find randomised controlled trial (RCT) studies, with diet as the main focus, in MCI participants. The primary outcome was incident dementia and/or Alzheimer's disease (AD) and secondary outcomes included cognitive function across different domains using validated neuropsychological tests. Sixteen studies met the inclusion criteria. There was a high degree of heterogeneity relating to the nature of the dietary intervention and cognitive outcomes measured, thus making study comparisons difficult. Supplementation with vitamin E (one study, n 516), ginkgo biloba (one study, n 482) or Fortasyn Connect (one study, n 311) had no significant effect on progression from MCI to dementia and/or AD. For cognitive function, the findings showed some improvements in performance, particularly in memory, with the most consistent results shown by B vitamins, including folic acid (one study, n 266), folic acid alone (one study, n 180), DHA and EPA (two studies, n 36 and n 86), DHA (one study, n 240) and flavonol supplementation (one study, n 90). The findings indicate that dietary factors may have a potential benefit for cognitive function in MCI patients. Further well-designed trials are needed, with standardised and robust measures of cognition to investigate the influence of diet on cognitive status.

Objective To explore the role of chronic inflammation in rheumatoid arthritis (RA) on cognition. Methods and analysis Six hundred sixty-one men and women aged ≥55 years who fulfilled the American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) criteria for RA were recruited from three healthcare trusts in the United Kingdom (UK) between May 2018 and March 2020. Study participants took part in interviews which captured sociodemographic information, followed by an assessment of cognition. RA specific clinical characteristics were obtained from hospital medical records. Participants were cognitively assessed using the Montreal Cognitive Assessment (MoCA) and were classified as cognitively impaired if they scored ≤27/30 points. Linear regression analyses were conducted to identify which demographic and clinical variables were potential predictors of cognitive impairment. Results The average age of participants was 67.6 years and 67% (444/661) were women. 72% (458/634; 95% CI 0.69 to 0.76) of participants were classified as cognitively impaired (MoCA≤27). Greater cognitive impairment was associated with older age ( p  = .006), being male ( p  = .041) and higher disease activity score (DAS28) (with moderate (DAS28 > 3.1) ( p  = 0.008) and high (DAS28 > 5.1) ( p  = 0.008)) compared to those in remission (DAS28 ≤ 2.6). There was no association between MoCA score and education, disease duration, RF status, anti-cyclic citrullinated peptide (anti-CCP) status, RA medication type or use of glucocorticoids or non-steroidal anti-inflammatory drugs ( p  > 0.05). Conclusion This study suggests that cognitive impairment is highly prevalent in older adults with RA. This impairment appears to be associated with higher RA disease activity and supports the concept that chronic systemic inflammation might accelerate cognitive decline. This underlines the importance of controlling the inflammatory response.

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Alzheimer’s disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of AD pathology (Braak 0–6). Using high-resolution mass spectrometry, we employed a semi-targeted, fully quantitative lipidomics profiling method (Lipidyzer) to compare the biochemical profiles of brain tissues from persons with mild AD (n = 15) and severe AD (AD; n = 16), and compared them with age-matched, cognitively normal controls (n = 16). Univariate analysis revealed that the concentrations of 420 lipid metabolites significantly (p < 0.05; q < 0.05) differed between AD and controls. A total of 49 lipid metabolites differed between mild AD and controls, and 439 differed between severe AD and mild AD. Interestingly, 13 different subclasses of lipids were significantly perturbed, including neutral lipids, glycerolipids, glycerophospholipids, and sphingolipids. Diacylglycerol (DAG) (14:0/14:0), triacylglycerol (TAG) (58:10/FA20:5), and TAG (48:4/FA18:3) were the most notably altered lipids when AD and control brains were compared (p < 0.05). When we compare mild AD and control brains, phosphatidylethanolamine (PE) (p-18:0/18:1), phosphatidylserine (PS) (18:1/18:2), and PS (14:0/22:6) differed the most (p < 0.05). PE (p-18:0/18:1), DAG (14:0/14:0), and PS (18:1/20:4) were identified as the most significantly perturbed lipids when AD and mild AD brains were compared (p < 0.05). Our analysis provides the most extensive lipid profiling yet undertaken in AD brain tissue and reveals the cumulative perturbation of several lipid pathways with progressive disease pathology. Lipidomics has considerable potential for studying AD etiology and identifying early diagnostic biomarkers.

Introduction There is concern about the use of anticholinergic medications in people living with dementia (PLWD). Such medicines may increase cognitive decline and may be associated with higher mortality in PLWD who take these medicines. The aim of this study was to analyse data from an online dementia discussion forum to explore the experiences and perspectives of PLWD and carers about the use of anticholinergic medicines in this population. Methods Following receipt of ethical approval, archived discussions (posts) from Dementia Talking Point, a fully public online forum for anyone affected by dementia, created and maintained by the Alzheimer's Society, were searched from the date of inception to January 2022 using a range of search terms including commonly used anticholinergic medicines. Posts, including any of the search terms, were assessed for relevance and analysed using inductive thematic analysis. Results Five hundred and fifty unique posts were analysed, all of which had been provided by carers, with no posts attributed to PLWD. The themes that encompassed carers' experiences were (1) motivators of prescribing, (2) perspectives on the process of prescribing and (3) the outcomes of prescribing. The dominant motivator of prescribing was the management of noncognitive symptoms, pre‐ and postdiagnosis of dementia. Carers' perspectives on the process of prescribing were informed by an assessment of the risk‐benefit of starting a medication and shared decision‐making between the carer and healthcare professional to a greater or lesser degree. The outcomes of prescribing were observing the effects of the medicines, which in turn influenced whether prescribing was reviewed and continued unchanged, continued but amended, reinitiated if the medicine had been previously stopped or discontinued (the process of deprescribing). Conclusion This study has provided unique insights into carers' experiences and perspectives about the use of anticholinergic medications in PLWD, highlighting how commonly these medications are prescribed for PLWD and carers' concerns about their use. There is a clear need for carers and PLWD to receive information about these medicines and healthcare professionals to consider how to optimise the use of these medicines to avoid adverse effects. Patient or Public Contribution This work was informed by findings from previous research studies focusing on optimising medicine use for people with dementia in primary care, in which interviews were conducted with PLWD, their carers and primary healthcare professionals. Although not strictly patient and public involvement, we utilised the feedback provided by key stakeholders to inform the research questions and aim/objectives of this study.

Magnetic resonance imaging (MRI) and positron emission tomography (PET) are neuroimaging modalities typically used for evaluating brain changes in Alzheimer's disease (AD). Due to their complementary nature, their combination can provide more accurate AD diagnosis or prognosis. In this work, we apply a multi-modal imaging machine-learning framework to enhance AD classification and prediction of diagnosis of subject-matched gray matter MRI and Pittsburgh compound B (PiB)-PET data related to 58 AD, 108 mild cognitive impairment (MCI) and 120 healthy elderly (HE) subjects from the Australian imaging, biomarkers and lifestyle (AIBL) dataset. Specifically, we combined a Dartel algorithm to enhance anatomical registration with multi-kernel learning (MKL) technique, yielding an average of >95% accuracy for three binary classification problems: AD-vs.-HE, MCI-vs.-HE and AD-vs.-MCI, a considerable improvement from individual modality approach. Consistent with -contrasts, the MKL weight maps revealed known brain regions associated with AD, i.e., (para)hippocampus, posterior cingulate cortex and bilateral temporal gyrus. Importantly, MKL regression analysis provided excellent predictions of diagnosis of individuals by = 0.86. In addition, we found significant correlations between the MKL classification and delayed memory recall scores with = 0.62 ( < 0.01). Interestingly, outliers in the regression model for diagnosis were mainly converter samples with a higher likelihood of converting to the inclined diagnostic category. Overall, our work demonstrates the successful application of MKL with Dartel on combined neuromarkers from different neuroimaging modalities in the AIBL data. This lends further support in favor of machine learning approach in improving the diagnosis and risk prediction of AD.

Background The Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) is a prospective, longitudinal study of a representative cohort of older adults living in Northern Ireland, United Kingdom. Its aim is to explore the social, behavioural, economic and biological factors of ageing and how these factors change as people age. The study has been designed to maximize comparability with other international studies of ageing thereby facilitating cross-country comparisons. This paper provides an overview of the design and methodology of the health assessment which was carried out as part of Wave 1. Methods Three thousand, six hundred and fifty five community dwelling adults, aged 50 years and over participated in the health assessment as part of Wave 1 of NICOLA. The health assessment included a battery of measurements across various domains that addressed key indicators of ageing namely: physical function, vision and hearing, cognitive function, and cardiovascular health. This manuscript describes the scientific rationale for the choice of assessments, provides an overview of the core objective measures carried out in the health assessment and describes the differences in characteristics of participants who took part in the health assessment compared to those who did not take part. Results The manuscript highlights the importance of incorporating objective measures of health in population based studies as a means of complementing subjective measures and as a way to advance our understanding of the ageing process. The findings contextualize NICOLA as a data resource within Dementias Platform UK (DPUK), the Gateway to Global Ageing (G2G) and other existing networks of population based longitudinal studies of ageing. Conclusion This manuscript can help inform design considerations for other population based studies of ageing and facilitate cross-country comparative analysis of key life-course factors affecting healthy ageing such as educational attainment, diet, the accumulation of chronic conditions (including Alzheimer’s disease, dementia and cardiovascular disease) as well as welfare and retirement policies.

Background Many factors determine dietary intake in older adults, including physical health, psychological well-being and socio-economic status. Dental status may also be important. The aim was to examine how dental status impacts perceived ability to eat to certain foods, nutrient intake and nutritional status in UK older adults. Methods Data collected by the National Diet and Nutrition Survey Rolling Programme was analysed. A 4-day food diary assessed dietary intake, while a Computer Assisted Personal Interview collected socio-demographic, health behaviour and oral health information. Participants aged 65 years and over ( n  = 1053) were categorised into three groups according to their dental status: edentate with dentures (E-DEN, n  = 292), dentate with dentures (D-DEN, n  = 305) or dentate with no dentures (DEN, n  = 456). A total of 515 participants provided a blood sample that was used to assess nutrient concentrations including vitamin B12, vitamin C, ferritin, vitamin B6 (pyridoxal-5-phosphate, PLP), retinol, β-carotene and 25-hydroxyvitamin D (25-OH-D). Multiple regression methods were performed to examine cross-sectional associations between dental status, food selection, nutrient intake and nutritional status. Results Both E-DEN and D-DEN groups, compared with the DEN group, were more likely to report difficulty eating apples, raw carrots, lettuce, nuts, well-cooked steak and crusty bread ( P  < 0.01). No group differences were observed in perceived ability to eat sliced bread, sliced cooked meats and cheese. The E-DEN group compared with the DEN group had lower mean daily intakes of omega 3 fatty acids ( P  = 0.006), non-starch polysaccharides ( P  = 0.001), β-carotene ( P  = 0.001), folate ( P  = 0.001), vitamin C ( P  = 0.008), magnesium ( P  < 0.001) and potassium (P < 0.001), and had lower plasma vitamin B6 PLP ( P  = 0.001), vitamin C ( P  = 0.009) and β-carotene ( P  = 0.015) concentrations, after adjusting for socio-demographic and health behavioural factors. Compared with the DEN group, the D-DEN group did not have lower nutrient intakes or lower blood nutrient concentrations. Conclusions Within this sample of older adults, impaired dental status appears to influence food selection, and intake of important nutrients. Future research should focus on developing dental interventions coupled with dietary counselling to encourage the adoption of healthy eating habits in this high-risk population group.

IntroductionThe Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) study is the largest study of ageing in Northern Ireland (NI). The Harmonised Cognitive Assessment Protocol (HCAP) is a substudy of NICOLA designed to assess cognitive impairment and dementia in individuals aged 65 and over. The NICOLA-HCAP substudy is funded by the National Institute on Aging as part of a network for enhancing cross-national research within a worldwide group of population-based, longitudinal studies of ageing, all of which are centred around the US-based Health and Retirement Study.Methods and analysisThe NICOLA-HCAP study will draw on the main NICOLA cohort (of 8283 participants) and randomly sample 1000 participants aged 65 and over to take part in the substudy. Participants will complete a series of cognitive tests (n=19) via a computer-assisted personal interview administered in their home (or alternatively within the research centre) and will be asked to nominate a family member or friend to complete an additional interview of validated instruments to provide information on respondent’s prior and current cognitive and physical functioning and whether the individual requires help with daily activities. The objectives of the study are: to investigate the prevalence of dementia and cognitive impairment in NICOLA; harmonise scoring of the NICOLA-HCAP data to the HCAP studies conducted in Ireland, the USA and England; to explore the validity of dementia estimates; and investigate the risk factors for dementia and cognitive impairment.Ethics and disseminationThe study received ethical approval from the Faculty of Medicine, Health and Life Sciences Research Ethics Committee, Queen’s University Belfast. We will provide data from the Northern Irish HCAP to the research community via data repositories such as the Dementias Platform UK and Gateway to Global Aging to complement existing public data resources and support epidemiological research by others. Findings will also be disseminated through peer-reviewed publications and at international conferences.

Objectives Using blood derived DNA collected from individuals within the Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA), quantitative real-time polymerase chain reaction (RT-PCR) based absolute telomere length measures were derived in triplicate. This data is generated on a subset of participants ( n  = 2,971) within the NICOLA cohort at Wave 1 baseline. NICOLA commenced Wave 3 of data collection in Autumn 2024. Data description The NICOLA study recruited approximately 8,500 people from across Northern Ireland, with individuals recruited as representative of the Northern Ireland population. At recruitment, the NICOLA cohort was 45% male and 55% female. Adults were recruited over the age of 50, with approximately 50% of participants aged between 50 and 65, and 10% of participants over the age of 80. Telomere length (TL) values were determined for 2,971individuals (47.7% male) across 33 batches using the Absolute Human Telomere Length Quantification qPCR Assay kit and Roche LightCycler 480 II. Within-batch duplicate measures were established, as were water controls and non-template controls.