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Introduction: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β 1-42 (Aβ42)-positive status., Methods: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume., Results: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001)., Discussion: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter., Highlights: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objective: Examine the association between neuropsychiatric symptoms (NPS) and clinical outcome in memory clinic patients with vascular brain injury., Design/setting: TRACE-VCI prospective memory clinic cohort with follow-up (2.1 ± 0.5 years)., Participants: Five hundred and seventy-five memory clinic patients with vascular brain injury on MRI (i.e. possible Vascular Cognitive Impairment [VCI]). Severity of cognitive impairment ranged from no objective cognitive impairment to mild cognitive impairment (MCI) and dementia., Measurements: We used Neuropsychiatric Inventory (total score and score on hyperactive, psychotic, affective, and apathetic behavior domains) to measure NPS. We assessed the association between NPS and institutionalization, mortality and cognitive deterioration (increase ≥0.5 on Clinical Dementia Rating scale) with Cox proportional hazards models and logistic regression analyses., Results: NPS were present in 89% of all patients, most commonly in the hyperactive and apathetic behavior domain. Across the whole cohort, affective behavior was associated with institutionalization (HR: 1.98 [1.01-3.87]), mainly driven by the dementia subgroup (HR: 2.06 [1.00-4.21]). Apathetic behavior was associated with mortality and cognitive deterioration (HR: 2.07 [1.10-3.90],OR: 1.67 [1.12-2.49], respectively), mainly driven by the MCI subgroup (HR: 4.93 [1.07-22.86],OR: 3.25 [1.46-7.24], respectively). Conversely, hyperactive behavior was related to lower mortality (HR: 0.54 [0.29-0.98]), again particularly driven by the MCI subgroup (HR:0.17 [0.04-0.75]). Psychotic behavior was associated with cognitive deterioration in patients with no objective cognitive impairment (OR: 3.10 [1.09-8.80]) and with institutionalization in MCI (HR: 12.45 [1.28-121.14])., Conclusion: NPS are common and have prognostic value in memory clinic patients with possible VCI. This prognostic value depends on the severity of cognitive impairment., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Aim: To investigate the relationship between the diabetes-specific dementia risk score (DSDRS) and concurrent and future cognitive impairment (CI) in type 2 diabetes (T2D)., Methods: DSDRS were calculated for participants with T2D aged ≥60 years from the CARMELINA-cognition substudy (ClinicalTrials.gov Identifier: NCT01897532). Cognitive assessment included Mini-Mental State Examination (MMSE) and a composite attention and executive functioning score (A&E). The relation between baseline DSDRS and probability of CI (MMSE < 24) and variation in cognitive performance was assessed at baseline (n = 2241) and after 2.5 years follow-up in patients without baseline CI (n = 1312)., Results: Higher DSDRS was associated with a higher probability of CI at baseline (OR = 1.17 per point, 95% CI 1.12-1.22) and follow-up (OR = 1.24 per point, 95% CI 1.14-1.35). Moreover, in patients without baseline CI, higher DSDRS was also associated with lower baseline cognitive performance (MMSE: F(1, 1930) = 47.07, p < .0001, R 2  = 0.02); A&E z-score: (F(1, 1871) = 33.44 p < .0001, R 2  = 0.02) and faster cognitive decline at follow-up (MMSE: F(3, 1279) = 38.41, p < .0001; A&E z-score: F(3, 1206) = 148.48, p < .0001)., Conclusions: The DSDRS identifies patients with T2D at risk of concurrent as well as future CI. The DSDRS may thus be a supportive tool in screening strategies for cognitive dysfunction in patients with T2D., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: G.J.B.'s institution receives study grants from Boehringer Ingelheim. O.E.J. is an employee of Boehringer Ingelheim. No other potential conflicts of interest relevant to this article were reported., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: We investigated the association between white matter hyperintensity location and depressive symptoms in a memoryclinic population using lesion–symptom mapping., Methods: We included 680 patients with vascular brain injury from the TRACE-VCI cohort (mean age ± standard deviation: 67 ± 8 years; 52% female): 168 patients with subjective cognitive decline, 164 with mild cognitive impairment and 348 with dementia. We assessed depressive symptoms using the Geriatric Depression Scale. We applied assumptionfree voxel-based lesion–symptom mapping, adjusted for age, sex, total white matter hyperintensity volume and multiple testing. Next, we applied exploratory region-of-interest linear regression analyses of major white matter tracts, with additional adjustment for diagnosis., Results: Voxel-based lesion–symptom mapping identified voxel clusters related to the Geriatric Depression Scale in the left corticospinal tract. Region-of-interest analyses showed no relation between white matter hyperintensity volume and the Geriatric Depression Scale, but revealed an interaction with diagnosis in the forceps minor, where larger regional white matter hyperintensity volume was associated with more depressive symptoms in subjective cognitive decline (β = 0.26, p < 0.05), but not in mild cognitive impairment or dementia., Limitations: We observed a lack of convergence of findings between voxel-based lesion–symptom mapping and region-of-interest analyses, which may have been due to small effect sizes and limited lesion coverage despite the large sample size. This warrants replication of our findings and further investigation in other cohorts., Conclusion: This lesion–symptom mapping study in depressive symptoms indicates the corticospinal tract and forceps minor as strategic tracts in which white matter hyperintensity is associated with depressive symptoms in memory-clinic patients with vascular brain injury. The impact of white matter hyperintensity on depressive symptoms is modest, but it appears to depend on the location of white matter hyperintensity and disease severity., Competing Interests: N. Prins serves on the advisory board of Boehringer Ingelheim and Probiodrug, and on Abbvie’s DSMB M15-566 trial; has provided consultancy services for Sanofi, Takeda and Kyowa Kirin Pharmaceutical Development; receives research support from Alzheimer Nederland (project number WE.03-2012-02); and is the CEO and co-owner of Brain Research Centre, Amsterdam, the Netherlands. P. Scheltens has acquired grant support (for the institution) from GE Healthcare and Piramal; and in the past 2 years he has received consultancy/speaker fees (paid to the institution) from Medavante, Novartis, Probiodrug, Biogen, Roche, Toyama and EIP Pharma. F. Barkhof serves as a consultant for Biogen-Idec, Janssen Alzheimer Immunotherapy, Bayer-Schering, Merck-Serono, Roche, Novartis, Genzyme and Sanofi-aventis; has received sponsoring from EU-H2020, NWO, SMSR, TEVA, Novartis, Toshiba and Imi; and serves on the editorial boards of Radiology, Brain, Neuroradiology, MSJ and Neurology. Research programs of W.M. van der Flier have been funded by ZonMW, NWO, EU-FP7, Alzheimer Nederland, Cardiovasculair Onderzoek Nederland, Stichting Dioraphte, Gieskes-Strijbis fonds, Pasman Stichting, Boehringer Ingelheim, Piramal Imaging, Roche BV, Janssen Stellar, Biogen and Combinostics; all funding is paid to her institution. G. Biessels has been funded by the Dutch Heart Association, ZonMW, the Netherlands Organisation for Health Research and Development and European Union Horizon 2020. No other competing interests declared., (© 2019 Joule Inc. or its licensors)

Objective: Retinopathy impacts over one-third of those with diabetes mellitus and is associated with impaired cognitive performance and cerebrovascular lesions in middle-aged adults with type 1 diabetes. However, the association between diabetic retinopathy (DR) and risk of dementia in type 1 diabetes is unknown. We investigated the association between DR and incident dementia in a large, elderly population with type 1 diabetes., Methods: A cohort of 3742 patients with type 1 diabetes aged 50 years and above was followed from January 1, 1996 to September 30, 2015 for incident dementia. DR diagnoses were identified from electronic medical records. Age as timescale Cox proportional hazard models evaluated associations between time-updated DR and dementia risk. Models were adjusted for demographics, severe glycemic events, glycosylated hemoglobin, and vascular comorbidities., Results: Among 3742 patients with type 1 diabetes (47% female, 21% nonwhite), 182 (5%) were diagnosed with dementia during a mean follow-up of 6.2 years. No significant association was found between DR and incident dementia in the main analyses [adjusted Hazard Ratio=1.12; 95% confidence interval, 0.82-1.54), nor among subgroup restricted to those aged 60 years and above or 70 years and above., Conclusions: DR was not associated with risk of dementia, suggesting that pathophysiological processes underlying dementia may be different in type 1 versus type 2 diabetes.

Background: The metabolic syndrome (MetS) refers to a cluster of cardiovascular risk factors that is associated with an increased risk of cognitive impairment and dementia. It is unclear however, if the presence of the MetS is associated with a particular clinical profile or a different prognosis in patients with cognitive complaints or early dementia., Objectives: To compare 1) the clinical profile and 2) the prognosis of patients attending a memory clinic according to the presence or absence of MetS., Design: Longitudinal cohort., Setting: Memory clinic., Participants: We included and followed 86 consecutive patients (average age of 66.7 (SD 9.7)) from the Amsterdam Dementia Cohort with an MMSE>22., Measurements: Clinical profile (neuropsychological examination, brain MRI, cerebrospinal fluid (CSF) biomarkers, clinical diagnosis) on an initial standardized diagnostic assessment was compared according to MetS status. Progression to dementia was assessed in initially nondemented patients (subjective complaints n=40, mild cognitive impairment n=24, follow-up available in 59)., Results: 35 (41%) patients met the MetS criteria. Demographics were similar between patients with or without the MetS. At baseline, diagnosis, cognitive performance, severity of degenerative or vascular abnormalities on MRI, and CSF amyloid and tau levels did not differ between the groups (all p>0.05). Among nondemented patients, however, MetS was associated with worse performance on executive function, attention & speed and visuoconstructive ability (z-scores, p<0.05). During a mean follow-up of 3.4years a similar proportion of patients with (4; 17%) and without (6; 17%) the MetS progressed to dementia (p=0.45)., Conclusion: Among nondemented patients presenting at a memory clinic MetS was associated with slightly worse cognitive performance (worse on tasks assessing executive functions, visuo-constructive ability, attention & speed), but conversion rate to dementia was not increased., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Objective: The objective of this study was to obtain external validation of the only available midlife dementia risk score cardiovascular risk factors , aging and dementia study (CAIDE) constituting age, education, hypertension, obesity, and hyperlipidemia in a larger, more diverse population. Our second aim was to improve the CAIDE risk score by additional midlife risk factors., Methods: This retrospective cohort study was conducted in an integrated health care delivery system. A total of 9480 Kaiser Permanente members who participated in a health survey study (age range, 40-55 years) from 1964 to 1973 were included in this study. Dementia diagnoses from primary care and medical specialist visits were collected from January 1, 1994 to January 16, 2006, using International Classification of Diseases 9 codes 290.0, 290.1 for "possible dementia," and 331.0 and 290.4 for "specialist confirmed dementia." Risk model prediction and validation were examined with the C statistic, net reclassification improvement, and integrated discrimination improvement. Dementia risk per sum score was calculated with Kaplan-Meier estimates., Results: A total of 2767 participants (25%) were diagnosed with any type of dementia, of which 1011 diagnoses (10.7%) were specialist-confirmed diagnoses. Average time between midlife examination and end of follow-up was 36.1 years. The CAIDE risk score replicated well with a C statistic of 0.75, quite similar to the original CAIDE C statistic of 0.78. The CAIDE score also predicted well within different race strata. Other midlife risk factors (central obesity, depressed mood, diabetes mellitus, head trauma, lung function, and smoking) did not improve predictability. The risk score allowed stratification of participants into those with 40-year low (9%) and high (29%) dementia risk., Conclusions: A combination of modifiable vascular risk factors in midlife is highly predictive of the likelihood of dementia decades later. Possible dementia prevention strategies should point to a life course perspective on maintaining vascular health., (Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Background: Persons with type 2 diabetes are at an increased risk of dementia compared to those without, but the etiology of this increased risk is unclear., Objective: Cerebral microvascular disease may mediate the link between diabetes and dementia. Given the anatomical and physiological similarities between cerebral and retinal microvessels, we examined the longitudinal association between diabetic retinal disease and dementia in patients with type 2 diabetes., Methods: Longitudinal cohort study of 29,961 patients with type 2 diabetes aged ≥60 years. Electronic medical records were used to collect diagnoses and treatment of severe diabetic retinal disease (i.e., diabetic proliferative retinopathy and macular edema) between 1996-1998 and dementia diagnoses for the next ten years (1998-2008). The association between diabetic retinal disease and dementia was evaluated by Cox proportional hazard models adjusted for sociodemographics, as well as diabetes-specific (e.g., diabetes duration, pharmacotherapy, HbA1c, hypoglycemia, hyperglycemia) and vascular (e.g., vascular disease, smoking, body mass index) factors., Results: 2,008 (6.8%) patients had severe diabetic retinal disease at baseline and 5,173 (17.3%) participants were diagnosed with dementia during follow-up. Those with diabetic retinal disease had a 42% increased risk of incident dementia (demographics adjusted Hazards Ratio (HR) = 1.42, 95% Confidence Interval (CI) 1.27, 1.58); further adjustment for diabetes-specific (HR 1.29; 95% CI 1.14, 1.45) and vascular-related disease conditions (HR 1.35; 95% CI 1.21, 1.52) attenuated the relation slightly., Conclusion: Diabetic patients with severe diabetic retinal disease have an increased risk of dementia. This may reflect a causal link between microvascular disease and dementia.

Background: Although patients with type 2 diabetes are twice as likely to develop dementia as those without this disease, prediction of who has the highest future risk is difficult. We therefore created and validated a practical summary risk score that can be used to provide an estimate of the 10 year dementia risk for individuals with type 2 diabetes., Methods: Using data from two longitudinal cohorts of patients with type 2 diabetes (aged ≥60 years) with 10 years of follow-up, we created (n=29,961) and validated (n=2413) the risk score. We built our prediction model by evaluating 45 candidate predictors using Cox proportional hazard models and developed a point system for the risk score based on the size of the predictor's β coefficient. Model prediction was tested by discrimination and calibration methods. Dementia risk per sum score was calculated with Kaplan-Meier estimates., Findings: Microvascular disease, diabetic foot, cerebrovascular disease, cardiovascular disease, acute metabolic events, depression, age, and education were most strongly predictive of dementia and constituted the risk score (C statistic 0·736 for creation cohort and 0·746 for validation cohort). The dementia risk was 5·3% (95% CI 4·2-6·3) for the lowest score (-1) and 73·3% (64·8-81·8) for the highest (12-19) sum scores., Interpretation: To the best of our knowledge, this is the first risk score for the prediction of 10 year dementia risk in patients with type 2 diabetes mellitus. The risk score can be used to increase vigilance for cognitive deterioration and for selection of high-risk patients for participation in clinical trials., Funding: Kaiser Permanente Community Benefit, National Institute of Health, Utrecht University, ZonMw, and Fulbright., (Copyright © 2013 Elsevier Ltd. All rights reserved.)