Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank.

OBJECTIVES: Despite rising rates of multimorbidity, existing risk assessment tools are mostly limited to a single outcome of interest. This study tests the feasibility of producing multiple disease risk estimates with at least 70% discrimination (area under the receiver operating curve, AUROC) within the time and information constraints of the existing primary care health check framework. DESIGN: Observational prospective cohort study SETTING: UK Biobank. PARTICIPANTS: 228 240 adults from the UK population. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Myocardial infarction, atrial fibrillation, heart failure, stroke, all-cause dementia, chronic kidney disease, fatty liver disease, alcoholic liver disease, liver cirrhosis and liver failure. RESULTS: Using a set of predictors easily gathered at the standard primary care health check (such as the National Health Service Health Check), we demonstrate that it is feasible to simultaneously produce risk estimates for multiple disease outcomes with AUROC of 70% or greater. These predictors can be entered once into a single form and produce risk scores for stroke (AUROC 0.727, 95% CI 0.713 to 0.740), all-cause dementia (0.823, 95% CI 0.810 to 0.836), myocardial infarction (0.785, 95% CI 0.775 to 0.795), atrial fibrillation (0.777, 95% CI 0.768 to 0.785), heart failure (0.828, 95% CI 0.818 to 0.838), chronic kidney disease (0.774, 95% CI 0.765 to 0.783), fatty liver disease (0.766, 95% CI 0.753 to 0.779), alcoholic liver disease (0.864, 95% CI 0.835 to 0.894), liver cirrhosis (0.763, 95% CI 0.734 to 0.793) and liver failure (0.746, 95% CI 0.695 to 0.796). CONCLUSIONS: Easily collected diagnostics can be used to assess 10-year risk across multiple disease outcomes, without the need for specialist computing or invasive biomarkers. Such an approach could increase the utility of existing data and place multiorgan risk information at the fingertips of primary care providers, thus creating opportunities for longer-term multimorbidity prevention. Additional work is needed to validate whether these findings would hold in a larger, more representative cohort outside the UK Biobank.

Brain health measurement: a scoping review.

OBJECTIVES: Preservation of brain health is an urgent priority for the world's ageing population. The evidence base for brain health optimisation strategies is rapidly expanding, but clear recommendations have been limited by heterogeneity in measurement of brain health outcomes. We performed a scoping review to systematically evaluate brain health measurement in the scientific literature to date, informing development of a core outcome set. DESIGN: Scoping review. DATA SOURCES: Medline, APA PsycArticles and Embase were searched through until 25 January 2023. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies were included if they described brain health evaluation methods in sufficient detail in human adults and were in English language. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened titles, abstracts and full texts for inclusion and extracted data using Covidence software. RESULTS: From 6987 articles identified by the search, 727 studies met inclusion criteria. Study publication increased by 22 times in the last decade. Cohort study was the most common study design (n=609, 84%). 479 unique methods of measuring brain health were identified, comprising imaging, cognitive, mental health, biological and clinical categories. Seven of the top 10 most frequently used brain health measurement methods were imaging based, including structural imaging of grey matter and hippocampal volumes and white matter hyperintensities. Cognitive tests such as the trail making test accounted for 286 (59.7%) of all brain health measurement methods. CONCLUSIONS: The scientific literature surrounding brain health has increased exponentially, yet measurement methods are highly heterogeneous across studies which may explain the lack of clinical translation. Future studies should aim to develop a selected group of measures that should be included in all brain health studies to aid interstudy comparison (core outcome set), and broaden from the current focus on neuroimaging outcomes to include a range of outcomes.

NHS Health Check attendance is associated with reduced multiorgan disease risk: a matched cohort study in the UK Biobank.

BACKGROUND: The NHS Health Check is a preventive programme in the UK designed to screen for cardiovascular risk and to aid in primary disease prevention. Despite its widespread implementation, the effectiveness of the NHS Health Check for longer-term disease prevention is unclear. In this study, we measured the rate of new diagnoses in UK Biobank participants who underwent the NHS Health Check compared with those who did not. METHODS: Within the UK Biobank prospective study, 48,602 NHS Health Check recipients were identified from linked primary care records. These participants were then covariate-matched on an extensive range of socio-demographic, lifestyle, and medical factors with 48,602 participants without record of the check. Follow-up diagnoses were ascertained from health records over an average of 9 years (SD 2 years) including hypertension, diabetes, hypercholesterolaemia, stroke, dementia, myocardial infarction, atrial fibrillation, heart failure, fatty liver disease, alcoholic liver disease, liver cirrhosis, liver failure, acute kidney injury, chronic kidney disease (stage 3 +), cardiovascular mortality, and all-cause mortality. Time-varying survival modelling was used to compare adjusted outcome rates between the groups. RESULTS: In the immediate 2 years after the NHS Health Check, higher diagnosis rates were observed for hypertension, high cholesterol, and chronic kidney disease among health check recipients compared to their matched counterparts. However, in the longer term, NHS Health Check recipients had significantly lower risk across all multiorgan disease outcomes and reduced rates of cardiovascular and all-cause mortality. CONCLUSIONS: The NHS Health Check is linked to reduced incidence of disease across multiple organ systems, which may be attributed to risk modification through earlier detection and treatment of key risk factors such as hypertension and high cholesterol. This work adds important evidence to the growing body of research supporting the effectiveness of preventative interventions in reducing longer-term multimorbidity.

Binge-pattern alcohol consumption and genetic risk as determinants of alcohol-related liver disease.

Alcohol-related liver disease (ARLD) represents a major public health burden. Identification of high-risk individuals would allow efficient targeting of public health interventions. Here, we show significant interactions between pattern of drinking, genetic predisposition (polygenic risk score, PRS) and diabetes mellitus, and risk of incident ARLD, in 312,599 actively drinking adults in UK Biobank. Binge and heavy binge drinking significantly increase the risk of alcohol-related cirrhosis (ARC), with higher genetic predisposition further amplifying the risk. Further, we demonstrate a pronounced interaction between heavy binge drinking and high PRS, resulting in a relative excess risk due to interaction (RERI) of 6.07. Diabetes consistently elevates ARC risk across all drinking and PRS categories, and showed significant interaction with both binge patterns and genetic risk. Overall, we demonstrate synergistic effects of binge drinking, genetics, and diabetes on ARC, with potential to identify high-risk individuals for targeted interventions.

Development and validation of a dementia risk score in the UK Biobank and Whitehall II cohorts.

BACKGROUND: Current dementia risk scores have had limited success in consistently identifying at-risk individuals across different ages and geographical locations. OBJECTIVE: We aimed to develop and validate a novel dementia risk score for a midlife UK population, using two cohorts: the UK Biobank, and UK Whitehall II study. METHODS: We divided the UK Biobank cohort into a training (n=176 611, 80%) and test sample (n=44 151, 20%) and used the Whitehall II cohort (n=2934) for external validation. We used the Cox LASSO regression to select the strongest predictors of incident dementia from 28 candidate predictors and then developed the risk score using competing risk regression. FINDINGS: Our risk score, termed the UK Biobank Dementia Risk Score (UKBDRS), consisted of age, education, parental history of dementia, material deprivation, a history of diabetes, stroke, depression, hypertension, high cholesterol, household occupancy, and sex. The score had a strong discrimination accuracy in the UK Biobank test sample (area under the curve (AUC) 0.8, 95% CI 0.78 to 0.82) and in the Whitehall cohort (AUC 0.77, 95% CI 0.72 to 0.81). The UKBDRS also significantly outperformed three other widely used dementia risk scores originally developed in cohorts in Australia (the Australian National University Alzheimer's Disease Risk Index), Finland (the Cardiovascular Risk Factors, Ageing, and Dementia score), and the UK (Dementia Risk Score). CLINICAL IMPLICATIONS: Our risk score represents an easy-to-use tool to identify individuals at risk for dementia in the UK. Further research is required to determine the validity of this score in other populations.

Lifestyle-related risk factors and their cumulative associations with hippocampal and total grey matter volume across the adult lifespan: A pooled analysis in the European Lifebrain consortium.

BACKGROUND: Lifestyle-related risk factors, such as obesity, physical inactivity, short sleep, smoking and alcohol use, have been associated with low hippocampal and total grey matter volumes (GMV). However, these risk factors have mostly been assessed as separate factors, leaving it unknown if variance explained by these factors is overlapping or additive. We investigated associations of five lifestyle-related factors separately and cumulatively with hippocampal and total GMV, pooled across eight European cohorts. METHODS: We included 3838 participants aged 18-90 years from eight cohorts of the European Lifebrain consortium. Using individual person data, we performed cross-sectional meta-analyses on associations of presence of lifestyle-related risk factors separately (overweight/obesity, physical inactivity, short sleep, smoking, high alcohol use) as well as a cumulative unhealthy lifestyle score (counting the number of present lifestyle-related risk factors) with FreeSurfer-derived hippocampal volume and total GMV. Lifestyle-related risk factors were defined according to public health guidelines. RESULTS: High alcohol use was associated with lower hippocampal volume (r = -0.10, p = 0.021), and overweight/obesity with lower total GMV (r = -0.09, p = 0.001). Other lifestyle-related risk factors were not significantly associated with hippocampal volume or GMV. The cumulative unhealthy lifestyle score was negatively associated with total GMV (r = -0.08, p = 0.001), but not hippocampal volume (r = -0.01, p = 0.625). CONCLUSIONS: This large pooled study confirmed the negative association of some lifestyle-related risk factors with hippocampal volume and GMV, although with small effect sizes. Lifestyle factors should not be seen in isolation as there is evidence that having multiple unhealthy lifestyle factors is associated with a linear reduction in overall brain volume.

Association of gout with brain reserve and vulnerability to neurodegenerative disease.

Studies of neurodegenerative disease risk in gout are contradictory. Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain. Here we investigated associations between gout, brain structure, and neurodegenerative disease incidence. Gout patients had smaller global and regional brain volumes and markers of higher brain iron, using both observational and genetic approaches. Participants with gout also had higher incidence of all-cause dementia, Parkinson's disease, and probable essential tremor. Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis. These findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases. Motor and cognitive impairments may affect gout patients, particularly in early years after diagnosis.

Telomere length and brain imaging phenotypes in UK Biobank.

Telomeres form protective caps at the ends of chromosomes, and their attrition is a marker of biological aging. Short telomeres are associated with an increased risk of neurological and psychiatric disorders including dementia. The mechanism underlying this risk is unclear, and may involve brain structure and function. However, the relationship between telomere length and neuroimaging markers is poorly characterized. Here we show that leucocyte telomere length (LTL) is associated with multi-modal MRI phenotypes in 31,661 UK Biobank participants. Longer LTL is associated with: i) larger global and subcortical grey matter volumes including the hippocampus, ii) lower T1-weighted grey-white tissue contrast in sensory cortices, iii) white-matter microstructure measures in corpus callosum and association fibres, iv) lower volume of white matter hyperintensities, and v) lower basal ganglia iron. Longer LTL was protective against certain related clinical manifestations, namely all-cause dementia (HR 0.93, 95% CI: 0.91-0.96), but not stroke or Parkinson's disease. LTL is associated with multiple MRI endophenotypes of neurodegenerative disease, suggesting a pathway by which longer LTL may confer protective against dementia.

Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later.

Introduction: The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods: In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results: Postmenopausal females showed higher levels of baseline blood lipids (HDL ß = 0.14, p < 0.001, LDL ß = 0.20, p < 0.001, triglycerides ß = 0.12, p < 0.001) and HbA1c (ß = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (ß = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (ß = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (ß range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (ß = -0.27, p < 0.001). Discussion: Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.

Associations between moderate alcohol consumption, brain iron, and cognition in UK Biobank participants: Observational and mendelian randomization analyses.

BACKGROUND: Brain iron deposition has been linked to several neurodegenerative conditions and reported in alcohol dependence. Whether iron accumulation occurs in moderate drinkers is unknown. Our objectives were to investigate evidence in support of causal relationships between alcohol consumption and brain iron levels and to examine whether higher brain iron represents a potential pathway to alcohol-related cognitive deficits. METHODS AND FINDINGS: Observational associations between brain iron markers and alcohol consumption (n = 20,729 UK Biobank participants) were compared with associations with genetically predicted alcohol intake and alcohol use disorder from 2-sample mendelian randomization (MR). Alcohol intake was self-reported via a touchscreen questionnaire at baseline (2006 to 2010). Participants with complete data were included. Multiorgan susceptibility-weighted magnetic resonance imaging (9.60 ± 1.10 years after baseline) was used to ascertain iron content of each brain region (quantitative susceptibility mapping (QSM) and T2*) and liver tissues (T2*), a marker of systemic iron. Main outcomes were susceptibility (χ) and T2*, measures used as indices of iron deposition. Brain regions of interest included putamen, caudate, hippocampi, thalami, and substantia nigra. Potential pathways to alcohol-related iron brain accumulation through elevated systemic iron stores (liver) were explored in causal mediation analysis. Cognition was assessed at the scan and in online follow-up (5.82 ± 0.86 years after baseline). Executive function was assessed with the trail-making test, fluid intelligence with puzzle tasks, and reaction time by a task based on the "Snap" card game. Mean age was 54.8 ± 7.4 years and 48.6% were female. Weekly alcohol consumption was 17.7 ± 15.9 units and never drinkers comprised 2.7% of the sample. Alcohol consumption was associated with markers of higher iron (χ) in putamen (ß = 0.08 standard deviation (SD) [95% confidence interval (CI) 0.06 to 0.09], p < 0.001), caudate (ß = 0.05 [0.04 to 0.07], p < 0.001), and substantia nigra (ß = 0.03 [0.02 to 0.05], p < 0.001) and lower iron in the thalami (ß = -0.06 [-0.07 to -0.04], p < 0.001). Quintile-based analyses found these associations in those consuming >7 units (56 g) alcohol weekly. MR analyses provided weak evidence these relationships are causal. Genetically predicted alcoholic drinks weekly positively associated with putamen and hippocampus susceptibility; however, these associations did not survive multiple testing corrections. Weak evidence for a causal relationship between genetically predicted alcohol use disorder and higher putamen susceptibility was observed; however, this was not robust to multiple comparisons correction. Genetically predicted alcohol use disorder was associated with serum iron and transferrin saturation. Elevated liver iron was observed at just >11 units (88 g) alcohol weekly c.f. <7 units (56 g). Systemic iron levels partially mediated associations of alcohol intake with brain iron. Markers of higher basal ganglia iron associated with slower executive function, lower fluid intelligence, and slower reaction times. The main limitations of the study include that χ and T2* can reflect changes in myelin as well as iron, alcohol use was self-reported, and MR estimates can be influenced by genetic pleiotropy. CONCLUSIONS: To the best of our knowledge, this study represents the largest investigation of moderate alcohol consumption and iron homeostasis to date. Alcohol consumption above 7 units weekly associated with higher brain iron. Iron accumulation represents a potential mechanism for alcohol-related cognitive decline.

Alcohol consumption and MRI markers of brain structure and function: Cohort study of 25,378 UK Biobank participants.

Moderate alcohol consumption is widespread but its impact on brain structure and function is contentious. The relationship between alcohol intake and structural and functional neuroimaging indices, the threshold intake for associations, and whether population subgroups are at higher risk of alcohol-related brain harm remain unclear. 25,378 UK Biobank participants (mean age 54.9 ± 7.4 years, 12,254 female) underwent multi-modal MRI 9.6 ± 1.1 years after study baseline. Alcohol use was self-reported at baseline (2006-10). T1-weighted, diffusion weighted and resting state images were examined. Lower total grey matter volumes were observed in those drinking as little as 7-14 units (56-112 g) weekly. Higher alcohol consumption was associated with multiple markers of white matter microstructure, including lower fractional anisotropy, higher mean and radial diffusivity in a spatially distributed pattern across the brain. Associations between functional connectivity and alcohol intake were observed in the default mode, central executive, attention, salience and visual resting state networks. Relationships between total grey matter and alcohol were stronger than other modifiable factors, including blood pressure and smoking, and robust to unobserved confounding. Frequent binging, higher blood pressure and BMI steepened the negative association between alcohol and total grey matter volume. In this large observational cohort study, alcohol consumption was associated with multiple structural and functional MRI markers in mid- to late-life.

Subjective Cognitive Complaints Given in Questionnaire: Relationship With Brain Structure, Cognitive Performance and Self-Reported Depressive Symptoms in a 25-Year Retrospective Cohort Study.

BACKGROUND: Subjective cognitive complaints are common but it is unclear whether they indicate an underlying pathological process or reflect affective symptoms. METHOD: 800 community-dwelling older adults were drawn from the Whitehall II cohort. Subjective cognitive complaint inquiry for memory and concentration, a range of neuropsychological tests and multimodal MRI were performed in 2012-2016. Subjective complaints were again elicited after 1 year. Group differences in grey and white matter, between those with and without subjective complaints, were assessed using voxel-based morphometry and tract-based spatial statistics, respectively. Mixed effects models assessed whether cognitive decline or depressive symptoms (over a 25-year period) were associated with later subjective complaints. Analyses were controlled for potential confounders and multiple comparisons. RESULTS: Mean age of the sample at scanning was 69.8 years (±5.1, range: 60.3-84.6). Subjective memory complaints were common (41%) and predicted further similar complaints later (mean 1.4 ± 1.4 years). There were no group differences in grey matter density or white matter integrity. Subjective complaints were not cross-sectionally or longitudinally associated with objectively assessed cognition. However, those with subjective complaints reported higher depressive symptoms ("poor concentration": odds ratio = 1.12, 95% CI 1.07-1.18; "poor memory": odds ratio = 1.18, 1.12-1.24). CONCLUSIONS: In our sample subjective complaints were consistent over time and reflected depressive symptoms but not markers of neurodegenerative brain damage or concurrent or future objective cognitive impairment. Clinicians assessing patients presenting with memory complaints should be vigilant for affective disorders. These results question the rationale for including subjective complaints in a spectrum with Mild Cognitive Impairment diagnostic criteria.

Association of trajectories of depressive symptoms with vascular risk, cognitive function and adverse brain outcomes: The Whitehall II MRI sub-study.

BACKGROUND: Trajectories of depressive symptoms over the lifespan vary between people, but it is unclear whether these differences exhibit distinct characteristics in brain structure and function. METHODS: In order to compare indices of white matter microstructure and cognitive characteristics of groups with different trajectories of depressive symptoms, we examined 774 participants of the Whitehall II Imaging Sub-study, who had completed the depressive subscale of the General Health Questionnaire up to nine times over 25 years. Twenty-seven years after the first examination, participants underwent magnetic resonance imaging to characterize white matter hyperintensities (WMH) and microstructure and completed neuropsychological tests to assess cognition. Twenty-nine years after the first examination, participants completed a further cognitive screening test. OUTCOMES: Using K-means cluster modelling, we identified five trajectory groups of depressive symptoms: consistently low scorers ("low"; n = 505, 62·5%), a subgroup with an early peak in depression scores ("early"; n = 123, 15·9%), intermediate scorers ("middle"; n = 89, 11·5%), a late symptom subgroup with an increase in symptoms towards the end of the follow-up period ("late"; n = 29, 3·7%), and consistently high scorers ("high"; n = 28, 3·6%). The late, but not the consistently high scorers, showed higher mean diffusivity, larger volumes of WMH and impaired executive function. In addition, the late subgroup had higher Framingham Stroke Risk scores throughout the follow-up period, indicating a higher load of vascular risk factors. INTERPRETATION: Our findings suggest that tracking depressive symptoms in the community over time may be a useful tool to identify phenotypes that show different etiologies and cognitive and brain outcomes.

Alcohol use disorders and the brain.

A diagnosis of alcohol use disorder is associated with a higher risk of dementia, but a dose-response relationship between alcohol intake consumption and cognitive impairment remains unclear. Alcohol is associated with a range of effects on the central nervous system at different doses and acts on a number of receptors. Acute disorders include Wernicke's encephalopathy (WE), traumatic brain injury, blackouts, seizures, stroke and hepatic encephalopathy. The most common manifestations of chronic alcohol consumption are Korsakoff's syndrome (KS) and alcohol-related dementia (ARD). There is limited evidence for benefit from memantine in the treatment of ARD, but stronger evidence for the use of high-dose parenteral thiamine in the progression of neuropsychiatric symptoms for WE. Accumulating evidence exists for pharmacological treatment in the prevention of hepatic encephalopathy. Rehabilitation of people with ARD may take several years, and requires an approach that addresses physical and psychosocial factors.

Alcohol consumption is associated with reduced creatine levels in the hippocampus of older adults.

Besides its well established susceptibility to ageing, the hippocampus has also been shown to be affected by alcohol consumption. Proton spectroscopy (1H-MRS) of the hippocampus, particularly at high-field 7T MRI, may further our understanding of these associations. Here, we aimed to examine how hippocampal metabolites varied with age and alcohol consumption. Hippocampal metabolite spectra were acquired in 37 older adults using 7T 1H-MRS, from which we determined the absolute concentration of N-acetylaspartate (NAA), creatine, choline, myo-inositol, glutamate and glutamine. Thirty participants (mean age = 70.4 ± 4.7 years) also had self-reported data on weekly alcohol consumption. Total choline inversely correlated with age, although this did not survive multiple comparisons correction. Crucially, adults with a higher weekly alcohol consumption had significantly lower levels of creatine, suggesting a deficit in their hippocampal metabolism. These findings add to an increasing body of evidence linking alcohol to hippocampal function.

Association of Midlife Cardiovascular Risk Profiles With Cerebral Perfusion at Older Ages.

Importance: Poor cardiovascular health is an established risk factor for dementia, but little is known about its association with brain physiology in older adults. Objective: To examine the association of cardiovascular risk factors, measured repeatedly during a 20-year period, with cerebral perfusion at older ages. Design, Setting, and Participants: In this longitudinal cohort study, individuals were selected from the Whitehall II Imaging Substudy. Participants were included if they had no clinical diagnosis of dementia, had no gross brain structural abnormalities on magnetic resonance imaging scans, and had received pseudocontinuous arterial spin labeling magnetic resonance imaging. Cardiovascular risk was measured at 5-year intervals across 5 phases from September 1991 to October 2013. Arterial spin labeling scans were acquired between April 2014 and December 2014. Data analysis was performed from June 2016 to September 2018. Exposures: Framingham Risk Score (FRS) for cardiovascular disease, comprising age, sex, high-density lipoprotein cholesterol level, total cholesterol level, systolic blood pressure, use of antihypertensive medications, cigarette smoking, and diabetes, was assessed at 5 visits. Main Outcomes and Measures: Cerebral blood flow (CBF; in milliliters per 100 g of tissue per minute) was quantified with pseudocontinuous arterial spin labeling magnetic resonance imaging. Results: Of 116 adult participants, 99 (85.3%) were men. At the first examination, mean (SD) age was 47.1 (5.0) years; at the last examination, mean (SD) age was 67.4 (4.9) years. Mean (SD) age at MRI scan was 69.3 (5.0) years. Log-FRS increased with time (B = 0.058; 95% CI, 0.044 to 0.072; P < .001). Higher cumulative FRS over the 20-year period (measured as the integral of the rate of change of log-FRS) was associated with lower gray matter CBF (B = -0.513; 95% CI -0.802 to -0.224; P < .001) after adjustment for age, sex, education, socioeconomic status, cognitive status, arterial transit time, use of statins, and weekly alcohol consumption. Voxelwise analyses revealed that this association was significant in 39.6% of gray matter regions, including the posterior cingulate, precuneus, lateral parietal cortex, occipital cortex, hippocampi, and parahippocampal gyrus. The strength of the association of higher log-FRS with lower CBF decreased progressively from the first examination (R2 = 0.253; B = -10.816; 99% CI -18.375 to -3.257; P < .001) to the last (R2 = 0.188; B = -7.139; 99% CI -14.861 to 0.582; P = .02), such that the most recent FRS measurement at mean (SD) age 67.4 (4.9) years was not significantly associated with CBF with a Bonferroni-corrected P < .01 . Conclusions and Relevance: Cardiovascular risk in midlife was significantly associated with lower gray matter perfusion at older ages, but this association was not significant for cardiovascular risk in later life. This finding could inform the timing of cardiovascular interventions so as to be optimally effective.

Predicting cognitive resilience from midlife lifestyle and multi-modal MRI: A 30-year prospective cohort study.

BACKGROUND: There is significant heterogeneity in the clinical expression of structural brain abnormalities, including Alzheimer's disease biomarkers. Some individuals preserve their memory despite the presence of risk factors or pathological brain changes, indicating resilience. We aimed to test whether resilient individuals could be distinguished from those who develop cognitive impairment, using sociodemographic variables and neuroimaging. METHODS: We included 550 older adults participating in the Whitehall II study with longitudinal data, cognitive test results, and multi-modal MRI. Hippocampal atrophy was defined as Scheltens Scores >0. Resilient individuals (n = 184) were defined by high cognitive performance despite hippocampal atrophy (HA). Non-resilient participants (n = 133) were defined by low cognitive performance (≥1.5 standard deviations (S.D.) below the group mean) in the presence of HA. Dynamic and static exposures were evaluated for their ability to predict later resilience status using multivariable logistic regression. In a brain-wide analysis we tested for group differences in the integrity of white matter (structural connectivity) and resting-state networks (functional connectivity). FINDINGS: Younger age (OR: 0.87, 95% CI: 0.83 to 0.92, p<0.001), higher premorbid FSIQ (OR: 1.06, 95% CI: 1.03 to 1.10, p<0.0001) and social class (OR 1 vs. 3: 4.99, 95% CI: 1.30 to 19.16, p = 0.02, OR 2 vs. 3: 8.43, 95% CI: 1.80 to 39.45, p = 0.007) were independently associated with resilience. Resilient individuals could be differentiated from non-resilient participants by higher fractional anisotropy (FA), and less association between anterior and posterior resting state networks. Higher FA had a significantly more positive effect on cognitive performance in participants with HA, compared to those without. CONCLUSIONS: Resilient individuals could be distinguished from those who developed impairments on the basis of sociodemographic characteristics, brain structural and functional connectivity, but not midlife lifestyles. There was a synergistic deleterious effect of hippocampal atrophy and poor white matter integrity on cognitive performance. Exploiting and supporting neural correlates of resilience could offer a fresh approach to postpone or avoid the appearance of clinical symptoms.

Aggressive Behaviors in Alzheimer Disease and Mild Cognitive Impairment: Systematic Review and Meta-Analysis.

OBJECTIVE: We aim to estimate the risk of perpetrating aggression in Alzheimer disease (AD) and mild cognitive impairment (MCI) by conducting a systematic review and meta-analysis of primary studies. METHODS: A systematic search was conducted in six bibliographic databases according to a preregistered protocol. Studies that reported aggressive behaviors in individuals with AD and MCI compared with healthy individuals or those with other dementia etiologies were identified. Risks of aggressive behaviors were assessed using random effects models to calculate pooled odds ratios (ORs). Publication bias was examined. RESULTS: In total, 17 studies involving 6,399 individuals with AD and 2,582 with MCI were identified. Compared with healthy individuals, significantly increased risks of aggressive behaviors were found in AD (OR, 4.9, 95% CI, 1.8-13.2) but not in MCI (OR, 1.8, 95% CI, 0.7-4.3). When comparing AD with MCI, the risk in AD was higher (OR, 2.6, 95% CI, 1.7-4.0). We found no differences in risk of aggressive behaviors between AD and other dementia subtypes or between amnestic and nonamnestic MCI. CONCLUSION: Individuals with AD are at higher risk of manifesting aggressive behaviors than healthy individuals or those with MCI. Our findings not only underscore the necessity of treatment of aggressive behaviors in AD but also highlight the importance of preventing the transition from MCI to AD.

Prescribing antipsychotics in older people: A mini-review.

Antipsychotic medications are widely prescribed in elderly populations for a range of psychiatric symptoms. Evidence for their efficacy in this population is limited, and such individuals are at increased risk of numerous side-effects, including stroke and death, particularly in those with dementia. There appears to be a mismatch between the current evidence base and what is occurring in clinical practice, especially in the use of antipsychotics to treat delirium and behavioural and psychological disturbance in dementia. We advise caution in the prescription of antipsychotics in older people and seeking specialist advice.

Classification and characterization of periventricular and deep white matter hyperintensities on MRI: A study in older adults.

White matter hyperintensities (WMH) are frequently divided into periventricular (PWMH) and deep (DWMH), and the two classes have been associated with different cognitive, microstructural, and clinical correlates. However, although this distinction is widely used in visual ratings scales, how to best anatomically define the two classes is still disputed. In fact, the methods used to define PWMH and DWMH vary significantly between studies, making results difficult to compare. The purpose of this study was twofold: first, to compare four current criteria used to define PWMH and DWMH in a cohort of healthy older adults (mean age: 69.58 ± 5.33 years) by quantifying possible differences in terms of estimated volumes; second, to explore associations between the two WMH sub-classes with cognition, tissue microstructure and cardiovascular risk factors, analysing the impact of different criteria on the specific associations. Our results suggest that the classification criterion used for the definition of PWMH and DWMH should not be considered a major obstacle for the comparison of different studies. We observed that higher PWMH load is associated with reduced cognitive function, higher mean arterial pressure and age. Higher DWMH load is associated with higher body mass index. PWMH have lower fractional anisotropy than DWMH, which also have more heterogeneous microstructure. These findings support the hypothesis that PWMH and DWMH are different entities and that their distinction can provide useful information about healthy and pathological aging processes.