Publications by authors named "Archana Singh-Manoux"

341 Publications

Comparison of the predictive accuracy of multiple definitions of cognitive impairment for incident dementia: a 20-year follow-up of the Whitehall II cohort study.

Lancet Healthy Longev 2021 Jul;2(7):e407-e416

Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Paris, France.

Background: Studies generally use cognitive assessment done at one timepoint to define cognitive impairment in order to examine conversion to dementia. Our objective was to examine the predictive accuracy and conversion rate of seven alternate definitions of cognitive impairment for dementia.

Methods: In this prospective study, we included participants from the Whitehall II cohort study who were assessed for cognitive impairment in 2007-09 and were followed up for clinically diagnosed dementia. Algorithms based on poor cognitive performance (defined using age-specific and sex-specific thresholds, and subsequently thresholds by education or occupation levels) and objective cognitive decline (using data from cognitive assessments in 1997-99, 2002-04, and 2007-09) were used to generate seven alternate definitions of cognitive impairment. We compared predictive accuracy using Royston's , the Akaike information criterion (AIC), sensitivity, specificity, and Harrell's C-statistic.

Findings: 5687 participants, with a mean age of 65·7 years (SD 5·9) in 2007-09, were included and followed up for a median of 10·5 years (IQR 10·1-10·9). Over follow-up, 270 (4·7%) participants were clinically diagnosed with dementia. Cognitive impairment defined using both cognitive performance and decline had higher hazard ratios (from 5·08 [95% CI 3·82-6·76] to 5·48 [4·13-7·26]) for dementia than did definitions based on cognitive performance alone (from 3·25 [2·52-4·17] to 3·39 [2·64-4·36]) and cognitive decline alone (3·01 [2·37-3·82]). However, all definitions had poor predictive performance (C-statistic ranged from 0·591 [0·565-0·616] to 0·631 [0·601-0·660]), primarily due to low sensitivity (21·6-48·4%). A predictive model containing age, sex, and education without measures of cognitive impairment had better predictive performance (C-statistic 0·783 [0·758-0·809], sensitivity 74·2%, specificity 72·2%) than all seven definitions of cognitive impairment (all p<0·0001).

Interpretation: These findings suggest that cognitive impairment in early old age might not be useful for dementia prediction, even when it is defined using longitudinal data on cognitive decline and thresholds of poor cognitive performance additionally defined by education or occupation.

Funding: National Institutes of Health, UK Medical Research Council.
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http://dx.doi.org/10.1016/S2666-7568(21)00117-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245324PMC
July 2021

Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study.

Lancet Digit Health 2021 Jul;3(7):e434-e444

Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland; Department of Epidemiology and Public Health, University College London, London, UK.

Background: Evaluation of cardiovascular disease risk in primary care, which is recommended every 5 years in middle-aged and older adults (typical age range 40-75 years), is based on risk scores, such as the European Society of Cardiology Systematic Coronary Risk Evaluation (SCORE) and American College of Cardiology/American Heart Association Atherosclerotic Cardiovascular Disease (ASCVD) algorithms. This evaluation currently uses only the most recent risk factor assessment. We aimed to examine whether 5-year changes in SCORE and ASCVD risk scores are associated with future cardiovascular disease risk.

Methods: We analysed data from the Whitehall II longitudinal, prospective cohort study for individuals with no history of stroke, myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, definite angina, heart failure, or peripheral artery disease. Participants underwent clinical examinations in 5-year intervals between Aug 7, 1991, and Dec 6, 2016, and were followed up for incident cardiovascular disease until Oct 2, 2019. Levels of, and 5-year changes in, cardiovascular disease risk were assessed using the SCORE and ASCVD risk scores and were analysed as predictors of cardiovascular disease. Harrell's C index, continuous net reclassification improvement, the Akaike information criterion, and calibration analysis were used to assess whether incorporating change in risk scores into a model including only a single risk score assessment improved the predictive performance. We assessed the levels of, and 5-year changes in, SCORE and ASCVD risk scores as predictors of cardiovascular disease and disease-free life-years using Cox proportional hazards and flexible parametric survival models.

Findings: 7574 participants (5233 [69·1%] men, 2341 [30·9%] women) aged 40-75 years were included in analyses of risk score change between April 24, 1997, and Oct 2, 2019. During a mean follow-up of 18·7 years (SD 5·5), 1441 (19·0%; 1042 [72·3%] men and 399 [27·7%] women) participants developed cardiovascular disease. Adding 5-year change in risk score to a model that included only a single risk score assessment improved model performance according to Harrell's C index (from 0·685 to 0·690, change 0·004 [95% CI 0·000 to 0·008] for SCORE; from 0·699 to 0·700, change 0·001 [0·000 to 0·003] for ASCVD), the Akaike information criterion (from 17 255 to 17 200, change -57 [95% CI -97 to -13] for SCORE; from 14 739 to 14 729, change -10 [-28 to 7] for ASCVD), and the continuous net reclassification index (0·353 [95% CI 0·234 to 0·447] for SCORE; 0·232 [0·030 to 0·344] for ASCVD). Both favourable and unfavourable changes in SCORE and ASCVD were associated with cardiovascular disease risk and disease-free life-years. The associations were seen in both sexes and all age groups up to the age of 75 years. At the age of 45 years, each 2-unit improvement in risk scores was associated with an additional 1·3 life-years (95% CI 0·4 to 2·2) free of cardiovascular disease for SCORE and an additional 0·9 life-years (95% CI 0·5 to 1·3) for ASCVD. At age 65 years, this same improvement was associated with an additional 0·4 life-years (95% CI 0·0 to 0·7) free of cardiovascular disease for SCORE and 0·3 life-years (95% CI 0·1 to 0·5) for ASCVD. These models were developed into an interactive calculator, which enables estimation of the number of cardiovascular disease-free life-years for an individual as a function of two risk score measurements.

Interpretation: Changes in the SCORE and ASCVD risk scores over time inform cardiovascular disease risk prediction beyond a single risk score assessment. Repeat data might allow more accurate cardiovascular risk stratification and strengthen the evidence base for decisions on preventive interventions.

Funding: UK Medical Research Council, British Heart Foundation, Wellcome Trust, and US National Institute on Aging.
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http://dx.doi.org/10.1016/S2589-7500(21)00079-0DOI Listing
July 2021

Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets.

Neuroimage 2021 08 20;237:118189. Epub 2021 May 20.

Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK. Electronic address:

Large scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise study sample differences contributing to differences in WMH variations across studies. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285593PMC
August 2021

Association Between Age at Diabetes Onset and Subsequent Risk of Dementia.

JAMA 2021 04;325(16):1640-1649

Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Inserm U1153, Paris, France.

Importance: Trends in type 2 diabetes show an increase in prevalence along with younger age of onset. While vascular complications of early-onset type 2 diabetes are known, the associations with dementia remains unclear.

Objective: To determine whether younger age at diabetes onset is more strongly associated with incidence of dementia.

Design, Setting, And Participants: Population-based study in the UK, the Whitehall II prospective cohort study, established in 1985-1988, with clinical examinations in 1991-1993, 1997-1999, 2002-2004, 2007-2009, 2012-2013, and 2015-2016, and linkage to electronic health records until March 2019. The date of final follow-up was March 31, 2019.

Exposures: Type 2 diabetes, defined as a fasting blood glucose level greater than or equal to 126 mg/dL at clinical examination, physician-diagnosed type 2 diabetes, use of diabetes medication, or hospital record of diabetes between 1985 and 2019.

Main Outcomes And Measures: Incident dementia ascertained through linkage to electronic health records.

Results: Among 10 095 participants (67.3% men; aged 35-55 years in 1985-1988), a total of 1710 cases of diabetes and 639 cases of dementia were recorded over a median follow-up of 31.7 years. Dementia rates per 1000 person-years were 8.9 in participants without diabetes at age 70 years, and rates were 10.0 per 1000 person-years for participants with diabetes onset up to 5 years earlier, 13.0 for 6 to 10 years earlier, and 18.3 for more than 10 years earlier. In multivariable-adjusted analyses, compared with participants without diabetes at age 70, the hazard ratio (HR) of dementia in participants with diabetes onset more than 10 years earlier was 2.12 (95% CI, 1.50-3.00), 1.49 (95% CI, 0.95-2.32) for diabetes onset 6 to 10 years earlier, and 1.11 (95% CI, 0.70-1.76) for diabetes onset 5 years earlier or less; linear trend test (P < .001) indicated a graded association between age at onset of type 2 diabetes and dementia. At age 70, every 5-year younger age at onset of type 2 diabetes was significantly associated with an HR of dementia of 1.24 (95% CI, 1.06-1.46) in analyses adjusted for sociodemographic factors, health behaviors, and health-related measures.

Conclusions And Relevance: In this longitudinal cohort study with a median follow-up of 31.7 years, younger age at onset of diabetes was significantly associated with higher risk of subsequent dementia.
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http://dx.doi.org/10.1001/jama.2021.4001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080220PMC
April 2021

Association of sleep duration in middle and old age with incidence of dementia.

Nat Commun 2021 04 20;12(1):2289. Epub 2021 Apr 20.

Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Paris, France.

Sleep dysregulation is a feature of dementia but it remains unclear whether sleep duration prior to old age is associated with dementia incidence. Using data from 7959 participants of the Whitehall II study, we examined the association between sleep duration and incidence of dementia (521 diagnosed cases) using a 25-year follow-up. Here we report higher dementia risk associated with a sleep duration of six hours or less at age 50 and 60, compared with a normal (7 h) sleep duration, although this was imprecisely estimated for sleep duration at age 70 (hazard ratios (HR) 1.22 (95% confidence interval 1.01-1.48), 1.37 (1.10-1.72), and 1.24 (0.98-1.57), respectively). Persistent short sleep duration at age 50, 60, and 70 compared to persistent normal sleep duration was also associated with a 30% increased dementia risk independently of sociodemographic, behavioural, cardiometabolic, and mental health factors. These findings suggest that short sleep duration in midlife is associated with an increased risk of late-onset dementia.
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http://dx.doi.org/10.1038/s41467-021-22354-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058039PMC
April 2021

Study Protocol: The Heart and Brain Study.

Front Physiol 2021 31;12:643725. Epub 2021 Mar 31.

Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Background: It is well-established that what is good for the heart is good for the brain. Vascular factors such as hypertension, diabetes, and high cholesterol, and genetic factors such as the apolipoprotein E4 allele increase the risk of developing both cardiovascular disease and dementia. However, the mechanisms underlying the heart-brain association remain unclear. Recent evidence suggests that impairments in vascular phenotypes and cerebrovascular reactivity (CVR) may play an important role in cognitive decline. The combines state-of-the-art vascular ultrasound, cerebrovascular magnetic resonance imaging (MRI) and cognitive testing in participants of the long-running Whitehall II Imaging cohort to examine these processes together. This paper describes the study protocol, data pre-processing and overarching objectives.

Methods And Design: The 775 participants of the Whitehall II Imaging cohort, aged 65 years or older in 2019, have received clinical and vascular risk assessments at 5-year-intervals since 1985, as well as a 3T brain MRI scan and neuropsychological tests between 2012 and 2016 (Whitehall II Wave MRI-1). Approximately 25% of this cohort are selected for the , which involves a single testing session at the University of Oxford (Wave MRI-2). Between 2019 and 2023, participants will undergo ultrasound scans of the ascending aorta and common carotid arteries, measures of central and peripheral blood pressure, and 3T MRI scans to measure CVR in response to 5% carbon dioxide in air, vessel-selective cerebral blood flow (CBF), and cerebrovascular lesions. The structural and diffusion MRI scans and neuropsychological battery conducted at Wave MRI-1 will also be repeated. Using this extensive life-course data, the will examine how 30-year trajectories of vascular risk throughout midlife (40-70 years) affect vascular phenotypes, cerebrovascular health, longitudinal brain atrophy and cognitive decline at older ages.

Discussion: The study will generate one of the most comprehensive datasets to examine the longitudinal determinants of the heart-brain association. It will evaluate novel physiological processes in order to describe the optimal window for managing vascular risk in order to delay cognitive decline. Ultimately, the will inform strategies to identify at-risk individuals for targeted interventions to prevent or delay dementia.
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http://dx.doi.org/10.3389/fphys.2021.643725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046163PMC
March 2021

Serum transthyretin and risk of cognitive decline and dementia: 22-year longitudinal study.

Neurol Sci 2021 Mar 26. Epub 2021 Mar 26.

Department of Epidemiology and Public Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.

Serum transthyretin (TTR) may be an early biomarker for Alzheimer's disease and related disorders (ADRD). We investigated associations of TTR measured at baseline with cognitive decline and incident ADRD and whether TTR trajectories differ between ADRD cases and non-cases, over 22 years before diagnosis. A total of 6024 adults aged 45-69 in 1997-1999 were followed up until 2019. TTR was assessed three times, and 297 cases of dementia were recorded. Higher TTR was associated with higher cognitive function at baseline; however, TTR was unrelated to subsequent change in cognitive function. TTR at baseline did not predict ADRD risk (hazard ratio per SD TTR (4.8 mg/dL) = 0.97; 95% confidence interval: 0.94-1.00). Among those later diagnosed with ADRD, there was a marginally steeper downward TTR trajectory than those free of ADRD over follow-up (P=0.050). Our findings suggest TTR is not neuroprotective. The relative decline in TTR level in the preclinical stage of ADRD is likely to be a consequence of disease processes.
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http://dx.doi.org/10.1007/s10072-021-05191-5DOI Listing
March 2021

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

Neuroimage Clin 2021 7;30:102616. Epub 2021 Mar 7.

Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.

White matter hyperintensities (WMHs) on T-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T-weighted images (Tw) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and Tw-hypointense/nonTw-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular Tw-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in Tw reveals specific associations with cognitive performance.
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http://dx.doi.org/10.1016/j.nicl.2021.102616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995650PMC
July 2021

Sex differences and the role of education in cognitive ageing: analysis of two UK-based prospective cohort studies.

Lancet Public Health 2021 02;6(2):e106-e115

Department of Epidemiology and Public Health, University College London, London, UK; Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Inserm U1153, Paris, France.

Background: Previous studies have shown an excess risk of Alzheimer's disease and related dementias among women. Education is thought to have a causal association with dementia onset. We aimed to investigate the role of education in influencing sex differences in cognitive ageing.

Methods: We analysed data from two prospective cohort studies in the UK; the English Longitudinal Study of Ageing (ELSA) and the Whitehall II study, to assess sex differences in cognitive performance and cognitive decline by birth cohort (birth year 1930-38, 1939-45, or 1946-55), before and after adjustment for education, and by high and low education level. Memory was assessed using immediate recall, for which data were available from all waves of the ELSA (2002-14) and Whitehall II (1997-2015) studies. Fluency was assessed using a semantic fluency test based on an animal naming task, with data available from all waves of the Whitehall II study and waves one to five (2002-10) and wave seven (2014) of the ELSA study. Cognitive scores were standardised separately in each study based on the mean and SD of the corresponding test among participants aged 50-59 years with secondary education.

Findings: 15 924 participants were included from the two studies. In pooled analyses, women had better memory scores than men in all birth cohorts, irrespective of adjustment for education (eg, at age 60 years, birth cohort 1930-38, mean difference between sexes [male scores minus female scores] -0·25 SDs [95% CI -0·32 to -0·19] after adjustment for education), and in both education level groups. Memory decline was faster in men than in women (at age 60 years, birth cohort 1946-55, mean difference in 13-year change -0·15 SDs [-0·20 to -0·09]; after adjustment for education -0·14 SDs [-0·20 to -0·08]). Men had better fluency scores than women in earlier birth cohorts and in the low education group (at age 60 years, birth cohort 1930-38, mean difference 0·20 SDs [95% CI 0·05 to 0·36]); but women had better fluency scores than men in later birth cohorts and in the high education group (at age 60 years, birth cohort 1946-55, mean difference -0·17 SDs [-0·24 to -0·10]). No sex differences were observed for fluency decline.

Interpretation: Our findings suggest that decreasing disparities between sexes in education, due to secular increases in educational opportunities, could attenuate sex differences in dementia risk and cognitive decline in the future.

Funding: National Institute on Aging, National Institutes of Health; UK Medical Research Council; British Heart Foundation; and National Institute for Health Research.
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http://dx.doi.org/10.1016/S2468-2667(20)30258-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141610PMC
February 2021

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory.

Int J Obes (Lond) 2021 Apr 14;45(4):758-765. Epub 2021 Jan 14.

Institute of Epidemiology and Health Care, University College London, London, UK.

Background/objectives: The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain.

Subjects/methods: We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of 'disinhibition', indicative of opportunistic eating or overeating and 'hunger' which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex.

Results: Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66-3.25 kg/m), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82-1.59 kg/m) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition.

Conclusions: Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.
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http://dx.doi.org/10.1038/s41366-020-00735-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005371PMC
April 2021

The association of APOE ε4 with cognitive function over the adult life course and incidence of dementia: 20 years follow-up of the Whitehall II study.

Alzheimers Res Ther 2021 01 4;13(1). Epub 2021 Jan 4.

Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Paris, France.

Background: Approximately 25% of the general population carries at least one ε4 allele of the Apolipoprotein E (APOE ε4), the strongest genetic risk factor for late onset Alzheimer's disease. Beyond its association with late-onset dementia, the association between APOE ε4 and change in cognition over the adult life course remains uncertain. This study aims to examine whether the association between Apolipoprotein E (APOE) ε4 zygosity and cognition function is modified between midlife and old age.

Methods: A cohort study of 5561 participants (mean age 55.5 (SD = 5.9) years, 27.1% women) with APOE genotyping and repeated cognitive tests for reasoning, memory, and semantic and phonemic fluency, during a mean (SD) follow-up of 20.2 (2.8) years (the Whitehall II study). We used joint models to examine the association of APOE genotype with cognitive function trajectories between 45 and 85 years taking drop-out, dementia, and death into account and Fine and Gray models to examine associations with dementia.

Results: Compared to non-carriers, heterozygote (prevalence 25%) and homozygote (prevalence 2%) APOE ε4 carriers had increased risk of dementia, sub-distribution hazard ratios 2.19 (95% CI 1.73, 2.77) and 5.97 (95% CI 3.85, 9.28) respectively. Using data spanning 45-85 years with non-ε4 carriers as the reference, ε4 homozygotes had poorer global cognitive score starting from 65 years; ε4 heterozygotes had better scores between 45 and 55 years, then no difference until poorer cognitive scores from 75 years onwards. In analysis of individual cognitive tests, better cognitive performance in the younger ε4 heterozygotes was primarily attributable to executive function.

Conclusions: Both heterozygous and homozygous ε4 carriers had poorer cognition and greater risk of dementia at older ages. Our findings show some support for a complex antagonist pleiotropic effect of APOE ε4 heterozygosity over the adult life course, characterized by cognitive advantage in midlife.
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http://dx.doi.org/10.1186/s13195-020-00740-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7784268PMC
January 2021

Associations between arterial stiffening and brain structure, perfusion, and cognition in the Whitehall II Imaging Sub-study: A retrospective cohort study.

PLoS Med 2020 12 29;17(12):e1003467. Epub 2020 Dec 29.

Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Background: Aortic stiffness is closely linked with cardiovascular diseases (CVDs), but recent studies suggest that it is also a risk factor for cognitive decline and dementia. However, the brain changes underlying this risk are unclear. We examined whether aortic stiffening during a 4-year follow-up in mid-to-late life was associated with brain structure and cognition in the Whitehall II Imaging Sub-study.

Methods And Findings: The Whitehall II Imaging cohort is a randomly selected subset of the ongoing Whitehall II Study, for which participants have received clinical follow-ups for 30 years, across 12 phases. Aortic pulse wave velocity (PWV) was measured in 2007-2009 (Phase 9) and at a 4-year follow-up in 2012-2013 (Phase 11). Between 2012 and 2016 (Imaging Phase), participants received a multimodal 3T brain magnetic resonance imaging (MRI) scan and cognitive tests. Participants were selected if they had no clinical diagnosis of dementia and no gross brain structural abnormalities. Voxel-based analyses were used to assess grey matter (GM) volume, white matter (WM) microstructure (fractional anisotropy (FA) and diffusivity), white matter lesions (WMLs), and cerebral blood flow (CBF). Cognitive outcomes were performance on verbal memory, semantic fluency, working memory, and executive function tests. Of 542 participants, 444 (81.9%) were men. The mean (SD) age was 63.9 (5.2) years at the baseline Phase 9 examination, 68.0 (5.2) at Phase 11, and 69.8 (5.2) at the Imaging Phase. Voxel-based analysis revealed that faster rates of aortic stiffening in mid-to-late life were associated with poor WM microstructure, viz. lower FA, higher mean, and radial diffusivity (RD) in 23.9%, 11.8%, and 22.2% of WM tracts, respectively, including the corpus callosum, corona radiata, superior longitudinal fasciculus, and corticospinal tracts. Similar voxel-wise associations were also observed with follow-up aortic stiffness. Moreover, lower mean global FA was associated with faster rates of aortic stiffening (B = -5.65, 95% CI -9.75, -1.54, Bonferroni-corrected p < 0.0125) and higher follow-up aortic stiffness (B = -1.12, 95% CI -1.95, -0.29, Bonferroni-corrected p < 0.0125). In a subset of 112 participants who received arterial spin labelling scans, faster aortic stiffening was also related to lower cerebral perfusion in 18.4% of GM, with associations surviving Bonferroni corrections in the frontal (B = -10.85, 95% CI -17.91, -3.79, p < 0.0125) and parietal lobes (B = -12.75, 95% CI -21.58, -3.91, p < 0.0125). No associations with GM volume or WMLs were observed. Further, higher baseline aortic stiffness was associated with poor semantic fluency (B = -0.47, 95% CI -0.76 to -0.18, Bonferroni-corrected p < 0.007) and verbal learning outcomes (B = -0.36, 95% CI -0.60 to -0.12, Bonferroni-corrected p < 0.007). As with all observational studies, it was not possible to infer causal associations. The generalisability of the findings may be limited by the gender imbalance, high educational attainment, survival bias, and lack of ethnic and socioeconomic diversity in this cohort.

Conclusions: Our findings indicate that faster rates of aortic stiffening in mid-to-late life were associated with poor brain WM microstructural integrity and reduced cerebral perfusion, likely due to increased transmission of pulsatile energy to the delicate cerebral microvasculature. Strategies to prevent arterial stiffening prior to this point may be required to offer cognitive benefit in older age.

Trial Registration: ClinicalTrials.gov NCT03335696.
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http://dx.doi.org/10.1371/journal.pmed.1003467DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771705PMC
December 2020

Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging.

Hum Brain Mapp 2021 Apr 14;42(6):1626-1640. Epub 2020 Dec 14.

Department of Psychiatry, University of Oxford, Oxford, UK.

The concept of brain maintenance refers to the preservation of brain integrity in older age, while cognitive reserve refers to the capacity to maintain cognition in the presence of neurodegeneration or aging-related brain changes. While both mechanisms are thought to contribute to individual differences in cognitive function among older adults, there is currently no "gold standard" for measuring these constructs. Using machine-learning methods, we estimated brain and cognitive age based on deviations from normative aging patterns in the Whitehall II MRI substudy cohort (N = 537, age range = 60.34-82.76), and tested the degree of correspondence between these constructs, as well as their associations with premorbid IQ, education, and lifestyle trajectories. In line with established literature highlighting IQ as a proxy for cognitive reserve, higher premorbid IQ was linked to lower cognitive age independent of brain age. No strong evidence was found for associations between brain or cognitive age and lifestyle trajectories from midlife to late life based on latent class growth analyses. However, post hoc analyses revealed a relationship between cumulative lifestyle measures and brain age independent of cognitive age. In conclusion, we present a novel approach to characterizing brain and cognitive maintenance in aging, which may be useful for future studies seeking to identify factors that contribute to brain preservation and cognitive reserve mechanisms in older age.
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http://dx.doi.org/10.1002/hbm.25316DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978127PMC
April 2021

Leisure activity participation and risk of dementia: An 18-year follow-up of the Whitehall II Study.

Neurology 2020 11 28;95(20):e2803-e2815. Epub 2020 Oct 28.

From the Division of Psychiatry (A.S., G. Livingston, G. Lewis) and Department of Epidemiology and Public Health (S.S., M.K., A.-S.M.), University College London; Camden and Islington NHS Foundation Trust (A.S., G. Livingston, G. Lewis), London, UK; Université de Paris (S.S., A.-S.M.), Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, France; and Clinicum and Helsinki Institute of Life Science (M.K.), University of Helsinki, Finland.

Objective: To test the hypothesis that leisure activity participation is associated with lower dementia risk, we examined the association between participation in leisure activities and incident dementia in a large longitudinal study with average 18-year follow-up.

Methods: We used data from 8,280 participants of the Whitehall II prospective cohort study. A 13-item scale assessed leisure activity participation in 1997-1999, 2002-2004, and 2007-2009, and incidence of dementia (n cases = 360, mean age at diagnosis 76.2 years, incidence rate 2.4 per 1,000 person-years) was ascertained from 3 comprehensive national registers with follow-up until March 2017. Primary analyses were based on complete cases (n = 6,050, n cases = 247) and sensitivity analyses used multiple imputation for missing data.

Results: Participation in leisure activities at mean age 55.8 (1997-1999 assessment), with 18.0-year follow-up, was not associated with dementia (hazard ratio [HR] 0.92 [95% confidence interval 0.79-1.06]), but those with higher participation at mean age 65.7 (2007-2009 assessment) were less likely to develop dementia with 8.3-year follow-up (HR 0.82 [0.69-0.98]). No specific type of leisure activity was consistently associated with dementia risk. Decline in participation between 1997-1999 and 2007-2009 was associated with subsequent dementia risk.

Conclusion: Our findings suggest that participation in leisure activities declines in the preclinical phase of dementia; there was no robust evidence for a protective association between leisure activity participation and dementia. Future research should investigate the sociobehavioral, cognitive, and neurobiological drivers of decline in leisure activity participation to determine potential approaches to improving social participation of those developing dementia.
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http://dx.doi.org/10.1212/WNL.0000000000010966DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734721PMC
November 2020

Timeline of pain before dementia diagnosis: a 27-year follow-up study.

Pain 2021 05;162(5):1578-1585

Inserm 1153, Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Paris, France.

Abstract: This study examines the importance of length of follow-up on the association between pain and incident dementia. Further objective was to characterize pain trajectories in the 27 years preceding dementia diagnosis and compare them with those among persons free of dementia during the same period. Pain intensity and pain interference (averaged as total pain) were measured on 9 occasions (1991-2016) using the Short-Form 36 Questionnaire amongst 9046 (women = 31.4%) dementia-free adults aged 40 to 64 years in 1991; 567 dementia cases were recorded between 1991 and 2019. Cox regression was used to assess the association between pain measures at different time points and incident dementia and mixed models to assess pain trajectories preceding dementia diagnosis or end point for dementia-free participants. Results from Cox regression showed moderate/severe compared with mild/no total pain, pain intensity, and pain interference not to be associated with dementia when the mean follow-up was 25.0, 19.6, 14.5, or 10.0 years. These associations were evident for a mean follow-up of 6.2 years: for total pain (hazard ratio = 1.72; 95% confidence intervals = 1.28-2.33), pain intensity (1.41; 1.04-1.92), and pain interference (1.80; 1.30-2.49). These associations were stronger when the mean follow-up for incidence of dementia was 3.2 years. Twenty-seven-year pain trajectories differed between dementia cases and noncases with small differences in total pain and pain interference evident 16 years before dementia diagnosis (difference in the total pain score = 1.4, 95% confidence intervals = 0.1-2.7) and rapidly increasing closer to diagnosis. In conclusion, these findings suggest that pain is a correlate or prodromal symptom rather than a cause of dementia.
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http://dx.doi.org/10.1097/j.pain.0000000000002080DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985036PMC
May 2021

Association of Changes in Cardiovascular Health Metrics and Risk of Subsequent Cardiovascular Disease and Mortality.

J Am Heart Assoc 2020 10 28;9(19):e017458. Epub 2020 Sep 28.

Department of Epidemiology INSERM U970 Paris Cardiovascular Research Center Paris France.

Background The extent to which change in cardiovascular health (CVH) in midlife reduces risk of subsequent cardiovascular disease and mortality is unclear. Methods and Results CVH was computed at 2 ARIC (Atherosclerosis Risk in Communities) study visits in 1987 to 1989 and 1993 to 1995, using 7 metrics (smoking, body mass index, total cholesterol, blood glucose, blood pressure, physical activity, and diet), each classified as poor, intermediate, and ideal. Overall CVH was classified as poor, intermediate, and ideal to correspond to 0 to 2, 3 to 4, and 5 to 7 metrics at ideal levels. There 10 038 participants, aged 44 to 66 years that were eligible. From the first to the second study visit, there was an improvement in overall CVH for 17% of participants and a decrease in CVH for 21% of participants. At both study visits, 28%, 27%, and 6% had poor, intermediate, and ideal overall CVH, respectively. Compared with those with poor CVH at both visits, the risk of cardiovascular disease (hazard ratio [HR], 0.26; 95% CI, 0.20-0.34) and mortality (HR, 0.35; 95% CI, 0.29-0.44) was lowest in those with ideal CVH at both measures. Improvement from poor to intermediate/ideal CVH was also associated with a lower risk of cardiovascular disease (HR, 0.67; 95% CI, 0.59-0.75) and mortality (HR, 0.80; 95% CI, 0.72-0.89). Conclusions Improvement in CVH or stable ideal CVH, compared with those with poor CVH over time, is associated with a lower risk of incident cardiovascular disease and all-cause mortality. The change in smoking status and cholesterol may have accounted for a large part of the observed association.
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http://dx.doi.org/10.1161/JAHA.120.017458DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7792367PMC
October 2020

Association of midlife stroke risk with structural brain integrity and memory performance at older ages: a longitudinal cohort study.

Brain Commun 2020 7;2(1):fcaa026. Epub 2020 Mar 7.

Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.

Cardiovascular health in midlife is an established risk factor for cognitive function later in life. Knowing mechanisms of this association may allow preventative steps to be taken to preserve brain health and cognitive performance in older age. In this study, we investigated the association of the Framingham stroke-risk score, a validated multifactorial predictor of 10-year risk of stroke, with brain measures and cognitive performance in stroke-free individuals. We used a large ( = 800) longitudinal cohort of community-dwelling adults of the Whitehall II imaging sub-study with no obvious structural brain abnormalities, who had Framingham stroke risk measured five times between 1991 and 2013 and MRI measures of structural integrity, and cognitive function performed between 2012 and 2016 [baseline mean age 47.9 (5.2) years, range 39.7-62.7 years; MRI mean age 69.81 (5.2) years, range 60.3-84.6 years; 80.6% men]. Unadjusted linear associations were assessed between the Framingham stroke-risk score in each wave and voxelwise grey matter density, fractional anisotropy and mean diffusivity at follow-up. These analyses were repeated including socio-demographic confounders as well as stroke risk in previous waves to examine the effect of residual risk acquired between waves. Finally, we used structural equation modelling to assess whether stroke risk negatively affects cognitive performance via specific brain measures. Higher unadjusted stroke risk measured at each of the five waves over 20 years prior to the MRI scan was associated with lower voxelwise grey and white matter measures. After adjusting for socio-demographic variables, higher stroke risk from 1991 to 2009 was associated with lower grey matter volume in the medial temporal lobe. Higher stroke risk from 1997 to 2013 was associated with lower fractional anisotropy along the corpus callosum. In addition, higher stroke risk from 2012 to 2013, sequentially adjusted for risk measured in 1991-94, 1997-98 and 2002-04 (i.e. 'residual risks' acquired from the time of these examinations onwards), was associated with widespread lower fractional anisotropy, and lower grey matter volume in sub-neocortical structures. Structural equation modelling suggested that such reductions in brain integrity were associated with cognitive impairment. These findings highlight the importance of considering cerebrovascular health in midlife as important for brain integrity and cognitive function later in life (ClinicalTrials.gov Identifier: NCT03335696).
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http://dx.doi.org/10.1093/braincomms/fcaa026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491431PMC
March 2020

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

J Psychiatr Res 2020 12 9;131:85-93. Epub 2020 Sep 9.

Department of Psychiatry, University of Oxford, Oxford, UK. Electronic address:

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.
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http://dx.doi.org/10.1016/j.jpsychires.2020.09.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063684PMC
December 2020

Association of Alcohol-Induced Loss of Consciousness and Overall Alcohol Consumption With Risk for Dementia.

JAMA Netw Open 2020 09 1;3(9):e2016084. Epub 2020 Sep 1.

Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Importance: Evidence on alcohol consumption as a risk factor for dementia usually relates to overall consumption. The role of alcohol-induced loss of consciousness is uncertain.

Objective: To examine the risk of future dementia associated with overall alcohol consumption and alcohol-induced loss of consciousness in a population of current drinkers.

Design, Setting, And Participants: Seven cohort studies from the UK, France, Sweden, and Finland (IPD-Work consortium) including 131 415 participants were examined. At baseline (1986-2012), participants were aged 18 to 77 years, reported alcohol consumption, and were free of diagnosed dementia. Dementia was examined during a mean follow-up of 14.4 years (range, 12.3-30.1). Data analysis was conducted from November 17, 2019, to May 23, 2020.

Exposures: Self-reported overall consumption and loss of consciousness due to alcohol consumption were assessed at baseline. Two thresholds were used to define heavy overall consumption: greater than 14 units (U) (UK definition) and greater than 21 U (US definition) per week.

Main Outcomes And Measures: Dementia and alcohol-related disorders to 2016 were ascertained from linked electronic health records.

Results: Of the 131 415 participants (mean [SD] age, 43.0 [10.4] years; 80 344 [61.1%] women), 1081 individuals (0.8%) developed dementia. After adjustment for potential confounders, the hazard ratio (HR) was 1.16 (95% CI, 0.98-1.37) for consuming greater than 14 vs 1 to 14 U of alcohol per week and 1.22 (95% CI, 1.01-1.48) for greater than 21 vs 1 to 21 U/wk. Of the 96 591 participants with data on loss of consciousness, 10 004 individuals (10.4%) reported having lost consciousness due to alcohol consumption in the past 12 months. The association between loss of consciousness and dementia was observed in men (HR, 2.86; 95% CI, 1.77-4.63) and women (HR, 2.09; 95% CI, 1.34-3.25) during the first 10 years of follow-up (HR, 2.72; 95% CI, 1.78-4.15), after excluding the first 10 years of follow-up (HR, 1.86; 95% CI, 1.16-2.99), and for early-onset (<65 y: HR, 2.21; 95% CI, 1.46-3.34) and late-onset (≥65 y: HR, 2.25; 95% CI, 1.38-3.66) dementia, Alzheimer disease (HR, 1.98; 95% CI, 1.28-3.07), and dementia with features of atherosclerotic cardiovascular disease (HR, 4.18; 95% CI, 1.86-9.37). The association with dementia was not explained by 14 other alcohol-related conditions. With moderate drinkers (1-14 U/wk) who had not lost consciousness as the reference group, the HR for dementia was twice as high in participants who reported having lost consciousness, whether their mean weekly consumption was moderate (HR, 2.19; 95% CI, 1.42-3.37) or heavy (HR, 2.36; 95% CI, 1.57-3.54).

Conclusions And Relevance: The findings of this study suggest that alcohol-induced loss of consciousness, irrespective of overall alcohol consumption, is associated with a subsequent increase in the risk of dementia.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.16084DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489835PMC
September 2020

Long-term risk of dementia following hospitalization due to physical diseases: A multicohort study.

Alzheimers Dement 2020 12 4;16(12):1686-1695. Epub 2020 Sep 4.

Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland.

Introduction: Conventional risk factors targeted by prevention (e.g., low education, smoking, and obesity) are associated with a 1.2- to 2-fold increased risk of dementia. It is unclear whether having a physical disease is an equally important risk factor for dementia.

Methods: In this exploratory multicohort study of 283,414 community-dwelling participants, we examined 22 common hospital-treated physical diseases as risk factors for dementia.

Results: During a median follow-up of 19 years, a total of 3416 participants developed dementia. Those who had erysipelas (hazard ratio = 1.82; 95% confidence interval = 1.53 to 2.17), hypothyroidism (1.94; 1.59 to 2.38), myocardial infarction (1.41; 1.20 to 1.64), ischemic heart disease (1.32; 1.18 to 1.49), cerebral infarction (2.44; 2.14 to 2.77), duodenal ulcers (1.88; 1.42 to 2.49), gastritis and duodenitis (1.82; 1.46 to 2.27), or osteoporosis (2.38; 1.75 to 3.23) were at a significantly increased risk of dementia. These associations were not explained by conventional risk factors or reverse causation.

Discussion: In addition to conventional risk factors, several physical diseases may increase the long-term risk of dementia.
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http://dx.doi.org/10.1002/alz.12167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754402PMC
December 2020

Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study.

Neuroimage 2020 11 21;222:117292. Epub 2020 Aug 21.

Department of Psychiatry, University of Oxford, Oxford, UK.

Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II (WHII) MRI cohort using machine learning and imaging-derived measures of gray matter (GM) morphology, white matter microstructure (WM), and resting state functional connectivity (FC). The results showed that the prediction accuracy improved when multiple imaging modalities were included in the model (R = 0.30, 95% CI [0.24, 0.36]). The modality-specific GM and WM models showed similar performance (R = 0.22 [0.16, 0.27] and R = 0.24 [0.18, 0.30], respectively), while the FC model showed the lowest prediction accuracy (R = 0.002 [-0.005, 0.008]), indicating that the FC features were less related to chronological age compared to structural measures. Follow-up analyses showed that FC predictions were similarly low in a matched sub-sample from UK Biobank, and although FC predictions were consistently lower than GM predictions, the accuracy improved with increasing sample size and age range. Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with brain aging in the WHII cohort. Blood pressure showed a stronger association with white matter compared to gray matter, while no differences in the associations of alcohol intake and stroke risk with these modalities were observed. In conclusion, machine-learning based brain age prediction can reduce the dimensionality of neuroimaging data to provide meaningful biomarkers of individual brain aging. However, model performance depends on study-specific characteristics including sample size and age range, which may cause discrepancies in findings across studies.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121758PMC
November 2020

Weight Management and Healthy Lifestyles-Reply.

JAMA Intern Med 2020 10;180(10):1404-1405

Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

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http://dx.doi.org/10.1001/jamainternmed.2020.2762DOI Listing
October 2020

Age and the association between apolipoprotein E genotype and Alzheimer disease: A cerebrospinal fluid biomarker-based case-control study.

PLoS Med 2020 08 20;17(8):e1003289. Epub 2020 Aug 20.

Department of Biochemistry and Molecular Biology, Lariboisière Hospital, APHP, Paris, France.

Background: The ε4 allele of apolipoprotein E (APOE) gene and increasing age are two of the most important known risk factors for developing Alzheimer disease (AD). The diagnosis of AD based on clinical symptoms alone is known to have poor specificity; recently developed diagnostic criteria based on biomarkers that reflect underlying AD neuropathology allow better assessment of the strength of the associations of risk factors with AD. Accordingly, we examined the global and age-specific association between APOE genotype and AD by using the A/T/N classification, relying on the cerebrospinal fluid (CSF) levels of β-amyloid peptide (A, β-amyloid deposition), phosphorylated tau (T, pathologic tau), and total tau (N, neurodegeneration) to identify patients with AD.

Methods And Findings: This case-control study included 1,593 white AD cases (55.4% women; mean age 72.8 [range = 44-96] years) with abnormal values of CSF biomarkers from nine European memory clinics and the American Alzheimer's Disease Neuroimaging Initiative (ADNI) study. A total of 11,723 dementia-free controls (47.1% women; mean age 65.6 [range = 44-94] years) were drawn from two longitudinal cohort studies (Whitehall II and Three-City), in which incident cases of dementia over the follow-up were excluded from the control population. Odds ratio (OR) and population attributable fraction (PAF) for AD associated with APOE genotypes were determined, overall and by 5-year age categories. In total, 63.4% of patients with AD and 22.6% of population controls carried at least one APOE ε4 allele. Compared with non-ε4 carriers, heterozygous ε4 carriers had a 4.6 (95% confidence interval 4.1-5.2; p < 0.001) and ε4/ε4 homozygotes a 25.4 (20.4-31.2; p < 0.001) higher OR of AD in unadjusted analysis. This association was modified by age (p for interaction < 0.001). The PAF associated with carrying at least one ε4 allele was greatest in the 65-70 age group (69.7%) and weaker before 55 years (14.2%) and after 85 years (22.6%). The protective effect of APOE ε2 allele for AD was unaffected by age. Main study limitations are that analyses were based on white individuals and AD cases were drawn from memory centers, which may not be representative of the general population of patients with AD.

Conclusions: In this study, we found that AD diagnosis based on biomarkers was associated with APOE ε4 carrier status, with a higher OR than previously reported from studies based on only clinical AD criteria. This association differs according to age, with the strongest effect at 65-70 years. These findings highlight the need for early interventions for dementia prevention to mitigate the effect of APOE ε4 at the population level.
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http://dx.doi.org/10.1371/journal.pmed.1003289DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446786PMC
August 2020

Associations Between Longitudinal Trajectories of Cognitive and Social Activities and Brain Health in Old Age.

JAMA Netw Open 2020 08 3;3(8):e2013793. Epub 2020 Aug 3.

Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.

Importance: Prior neuroimaging studies have found that late-life participation in cognitive (eg, reading) and social (eg, visiting friends and family) leisure activities are associated with magnetic resonance imaging (MRI) markers of the aging brain, but little is known about the neural and cognitive correlates of changes in leisure activities during the life span.

Objectives: To examine trajectories of cognitive and social activities from midlife to late life and evaluate whether these trajectories are associated with brain structure, functional connectivity, and cognition.

Design, Setting, And Participants: This prospective cohort included participants enrolled in the Whitehall II study and its MRI substudy based in the UK. Participants provided information on their leisure activities at 5 times during calendar years 1997 to 1999, 2002 to 2004, 2006, 2007 to 2009, and 2011 to 2013 and underwent MRI and cognitive battery testing from January 1, 2012, to December 31, 2016. Data analysis was performed from October 7, 2017, to July 15, 2019.

Main Outcome And Measures: Growth curve models and latent class growth analysis were used to identify longitudinal trajectories of cognitive and social activities. Multiple linear regression was used to evaluate associations between activity trajectories and gray matter, white matter microstructure, functional connectivity, and cognition.

Results: A total of 574 individuals (468 [81.5%] men; mean [SD] age, 69.9 [4.9] years; median Montreal Cognitive Assessment score, 28 [interquartile range, 26-28]) were included in the present analysis. During a mean (SD) of 15 (4.2) years, cognitive and social activity levels increased during midlife before reaching a plateau in late life. Both baseline (global cognition: unstandardized β [SE], 0.955 [0.285], uncorrected P = .001; executive function: β [SE], 1.831 [0.499], uncorrected P < .001; memory: β [SE], 1.394 [0.550], uncorrected P = .01; processing speed: β [SE], 1.514 [0.528], uncorrected P = .004) and change (global cognition: β [SE], -1.382 [0.492], uncorrected P = .005, executive function: β [SE], -2.219 [0.865], uncorrected P = .01; memory: β [SE], -2.355 [0.948], uncorrected P = .01) in cognitive activities were associated with multiple domains of cognition as well as global gray matter volume (β [SE], -0.910 [0.388], uncorrected P = .02). Baseline (β [SE], 1.695 [0.525], uncorrected P = .001) and change (β [SE], 2.542 [1.026], uncorrected P = .01) in social activities were associated only with executive function, in addition to voxelwise measures of functional connectivity that involved sensorimotor (quadratic change in social activities: number of voxels, 306; P = 0.01) and temporoparietal (linear change in social activities: number of voxels, 16; P = .02) networks. Otherwise, no voxelwise associations were found with gray matter, white matter, or resting-state functional connectivity. False discovery rate corrections for multiple comparisons suggested that the association between cognitive activity levels and executive function was robust (β [SE], 1.831 [0.499], false discovery rate P < .001).

Conclusions And Relevance: The findings suggest that a life course approach may delineate the association between leisure activities and cognitive and brain health and that interventions aimed at improving and maintaining cognitive engagement may be valuable for the cognitive health of community-dwelling older adults.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.13793DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7441365PMC
August 2020

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

Am J Geriatr Psychiatry 2021 03 7;29(3):217-226. Epub 2020 Jul 7.

Department of Psychiatry (AT, SS, CA,EZ, NF, CES, AM, CEM, KPE), University of Oxford, Oxford, UK.

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.
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http://dx.doi.org/10.1016/j.jagp.2020.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097240PMC
March 2021

Psychological Wellbeing and Aortic Stiffness: Longitudinal Study.

Hypertension 2020 09 13;76(3):675-682. Epub 2020 Jul 13.

From the Department of Epidemiology and Public Health, Institute of Epidemiology and Health, Faculty of Population Health Sciences, University College London, United Kingdom (A.I., A.S., M.S., A.S.-M., M.K., E.J.B.).

This study investigated 2 distinct aspects of positive wellbeing: affective wellbeing and eudaimonia with progression of aortic stiffness, an index of subclinical cardiovascular disease. A total of 4754 participants (mean age 65.3 years, 3466 men, and 1288 women) from the Whitehall II cohort study provided data on affective and eudaimonic wellbeing using subscales from the control, autonomy, self-realization and pleasure-19 questionnaire. Aortic stiffness was measured by aortic pulse wave velocity (PWV) at baseline (2008-2009) and 5 years later (2012-2013). Linear mixed models were used to measure the effect of affective and eudaimonic wellbeing on baseline PWV and 5-year PWV longitudinal change. A 1-SD higher eudaimonic wellbeing was associated with lower baseline PWV in men (β=-0.100 m/s [95% CI=-0.169 to -0.032]), independent of social, behavioral, and biological factors. This association persisted over 5 years. No such association was found in women (β=-0.029 m/s [95% CI=-0.126 to 0.069]). We did not find any association of positive wellbeing with change in PWV over time in either men or women. In older men, higher levels of eudaimonic wellbeing were associated with lower long-term levels of arterial stiffness. These findings support the notion that the pattern of association between positive wellbeing and cardiovascular health outcomes involves eudaimonic rather than affective wellbeing and is sex-specific.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.119.14284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418936PMC
September 2020

Healthy behaviors at age 50 years and frailty at older ages in a 20-year follow-up of the UK Whitehall II cohort: A longitudinal study.

PLoS Med 2020 07 6;17(7):e1003147. Epub 2020 Jul 6.

Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, France.

Background: Frailty is associated with increased risk of various health conditions, disability, and death. Health behaviors are thought to be a potential target for frailty prevention, but the evidence from previous studies is based on older populations with short follow-ups, making results susceptible to reverse causation bias. We examined the associations of healthy behaviors at age 50, singly and in combination, as well as 10-year change in the number of healthy behaviors over midlife with future risk of frailty.

Methods And Findings: In this prospective cohort study of 6,357 (29.2% women; 91.7% white) participants from the British Whitehall II cohort, healthy behaviors-nonsmoking, moderate alcohol consumption, ≥2.5 hours per week of moderate to vigorous physical activity, and consumption of fruits or vegetables at least twice a day-were measured at age 50, and change in behaviors was measured between 1985 (mean age = 44.4) and 1997 (mean age = 54.8). Fried's frailty phenotype was assessed in clinical examinations in 2002, 2007, 2012, and 2015. Participants were classified as frail if they had ≥3 of the following criteria: slow walking speed, low grip strength, weight loss, exhaustion, and low physical activity. An illness-death model accounting for both competing risk of death and interval censoring was used to examine the association between healthy behaviors and risk of frailty. Over an average follow-up of 20.4 years (standard deviation, 5.9), 445 participants developed frailty. Each healthy behavior at age 50 was associated with lower risk of incident frailty: hazard ratio (HR) after adjustment for other health behaviors and baseline characteristics 0.56 (95% confidence interval [CI] 0.44-0.71; p < 0.001) in nonsmokers, 0.73 (95% CI 0.61-0.88; p < 0.001) for moderate alcohol consumption, 0.66 (95% CI 0.54-0.81; p < 0.001) for ≥2.5 hours of physical activity per week, and 0.76 (95% CI 0.59-0.98; p = 0.03) for consumption of fruits or vegetables at least twice a day. A greater number of healthy behaviors was associated with reduced risk of frailty, with the HR for each additional healthy behavior being 0.69 (95% CI 0.62-0.76; p < 0.001) and the HR for having all versus no healthy behaviors at age 50 being 0.28 (95% CI 0.15-0.52; p < 0.001). Among participants with no or 1 healthy behavior in 1985, those who increased the number of healthy behaviors by 1997 were at a lower risk of frailty (mean follow-up = 16 years) compared with those with no such increase: the HR was 0.64 (95% CI 0.44-0.94; p = 0.02) for change to 2 healthy behaviors and 0.57 (95% CI 0.38-0.87; p < 0.001) for change to 3-4 healthy behaviors in 1997. The primary limitation of this study is potential selection bias during the follow-up due to missing data on frailty components.

Conclusions: Our findings suggest that healthy behaviors at age 50, as well as improvements in behaviors over midlife, are associated with a lower risk of frailty later in life. Their benefit accumulates so that risk of frailty decreases with greater number of healthy behaviors. These results suggest that healthy behaviors in midlife are a good target for frailty prevention.
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http://dx.doi.org/10.1371/journal.pmed.1003147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337284PMC
July 2020

Long-Term Greenspace Exposure and Progression of Arterial Stiffness: The Whitehall II Cohort Study.

Environ Health Perspect 2020 06 26;128(6):67014. Epub 2020 Jun 26.

ISGlobal, Barcelona, Spain.

Background: Arterial stiffness, and its progression with age, is an important indicator of cardiovascular aging. Greenspace exposure may protect against arterial stiffness by promoting physical activity, fostering social cohesion, and reducing stress and exposure to air pollution and noise.

Objectives: The aim of this study was to investigate the association of long-term exposure to outdoor greenspace with arterial stiffness and its progression over time.

Methods: This prospective cohort study was based on 4,349 participants (55-83 years of age) of the Whitehall II Study, United Kingdom. Arterial stiffness was assessed in two medical examinations (2007-2009 and 2012-2013) by measuring the carotid-femoral pulse wave velocity (cf-PWV). Residential surrounding greenspace was characterized using satellite-based indices of greenspace including normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and vegetation continuous fields (VCF) across buffers of 500 and surrounding the participants' residential locations at each follow-up. The association between the greenspace indicators and baseline cf-PWV and 4-year progression of cf-PWV was assessed using linear mixed-effects models with the participant as a random effect, controlling for demographic, lifestyle, and (individual and area) socioeconomic factors.

Results: No statistically significant associations were observed between residential surrounding greenspace and baseline or 4-y progression of cf-PWV; interquartile range (IQR) increases in NDVI, EVI, and VCF in the buffer were associated with [95% confidence interval (CI): , 0.04], (95% CI: , 0.05), and (95% CI: , 0.04) in baseline cf-PWV and (95% CI: , 0.14), (95% CI: , 0.14), and (95% CI: , 0.09) in 4-y progression in cf-PWV, respectively. The associations were similar when using buffers.

Conclusions: We did not observe any consistent association between residential surrounding greenspace and arterial stiffness. https://doi.org/10.1289/EHP6159.
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http://dx.doi.org/10.1289/EHP6159DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319656PMC
June 2020

Risk prediction models for dementia: role of age and cardiometabolic risk factors.

BMC Med 2020 05 19;18(1):107. Epub 2020 May 19.

Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 10 avenue de Verdun, 75010, Paris, France.

Background: Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score is the only currently available midlife risk score for dementia. We compared CAIDE to Framingham cardiovascular Risk Score (FRS) and FINDRISC diabetes score as predictors of dementia and assessed the role of age in their associations with dementia. We then examined whether these risk scores were associated with dementia in those free of cardiometabolic disease over the follow-up.

Methods: A total of 7553 participants, 39-63 years in 1991-1993, were followed for cardiometabolic disease (diabetes, coronary heart disease, stroke) and dementia (N = 318) for a mean 23.5 years. Cox regression was used to model associations of age at baseline, CAIDE, FRS, and FINDRISC risk scores with incident dementia. Predictive performance was assessed using Royston's R, Harrell's C-index, Akaike's information criterion (AIC), the Greenwood-Nam-D'Agostino (GND) test, and calibration-in-the-large. Age effect was also assessed by stratifying analyses by age group. Finally, in multistate models, we examined whether cardiometabolic risk scores were associated with incidence of dementia in persons who remained free of cardiometabolic disease over the follow-up.

Results: Among the risk scores, the predictive performance of CAIDE (C-statistic = 0.714; 95% CI 0.690-0.739) and FRS (C-statistic = 0.719; 95% CI 0.693-0.745) scores was better than FINDRISC (C-statistic = 0.630; 95% CI 0.602-0.659); p < 0.001), AIC difference > 3; R 32.5%, 32.0%, and 12.5%, respectively. When the effect of age in these risk scores was removed by drawing data on risk scores at age 55, 60, and 65 years, the association with dementia in all age groups remained for FRS and FINDRISC, but not for CAIDE. Only FRS at age 55 was associated with dementia in persons who remained free of cardiometabolic diseases prior to dementia diagnosis while no such association was observed at older ages for any risk score.

Conclusions: Our analyses of CAIDE, FRS, and FINDRISC show the FRS in midlife to predict dementia as well as the CAIDE risk score, its predictive value being also evident among individuals who did not develop cardiometabolic events. The importance of age in the predictive performance of all three risk scores highlights the need for the development of multivariable risk scores in midlife for primary prevention of dementia.
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http://dx.doi.org/10.1186/s12916-020-01578-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236124PMC
May 2020
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