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IntroductionLate-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.MethodsWe conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.ResultsWe identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.DiscussionMTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.HighlightsLong-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

BackgroundAlzheimer's Disease (AD) is a complex clinical phenotype with unprecedented social and economic tolls on an ageing global population. Real-world data (RWD) from electronic health records (EHRs) offer opportunities to accelerate precision drug development and scale epidemiological research on AD. A precise characterization of AD cohorts is needed to address the noise abundant in RWD.MethodsWe conducted a retrospective cohort study to develop and test computational models for AD cohort identification using clinical data from 8 Massachusetts healthcare systems. We mined temporal representations from EHR data using the transitive sequential pattern mining algorithm (tSPM) to train and validate our models. We then tested our models against a held-out test set from a review of medical records to adjudicate the presence of AD. We trained two classes of Machine Learning models, using Gradient Boosting Machine (GBM), to compare the utility of AD diagnosis records versus the tSPM temporal representations (comprising sequences of diagnosis and medication observations) from electronic medical records for characterizing AD cohorts.FindingsIn a group of 4985 patients, we identified 219 tSPM temporal representations (i.e., transitive sequences) of medical records for constructing the best classification models. The models with sequential features improved AD classification by a magnitude of 3-16 percent over the use of AD diagnosis codes alone. The computed cohort included 663 patients, 35 of whom had no record of AD. Six groups of tSPM sequences were identified for characterizing the AD cohorts.InterpretationWe present sequential patterns of diagnosis and medication codes from electronic medical records, as digital markers of Alzheimer's Disease. Classification algorithms developed on sequential patterns can replace standard features from EHRs to enrich phenotype modelling.FundingNational Institutes of Health: the National Institute on Aging (RF1AG074372) and the National Institute of Allergy and Infectious Diseases (R01AI165535).

The brain changes of Alzheimer's disease and other degenerative dementias begin long before cognitive dysfunction develops, and in people with subtle cognitive complaints, clinicians often struggle to predict who will develop dementia. The public increasingly sees benefits to accessing dementia risk evidence (DRE) such as biomarkers, predictive algorithms, and genetic information, particularly as this information moves from research to demonstrated usefulness in guiding diagnosis and clinical management. For example, the knowledge that one has high levels of amyloid in the brain may lead one to seek amyloid reducing medications, plan for disability, or engage in health promoting behaviors to fight cognitive decline. Researchers often hesitate to share DRE data, either because they are insufficiently validated or reliable for use in individuals, or there are concerns about assuring responsible use and ensuring adequate understanding of potential problems when one's biomarker status is known. Concerns include warning people receiving DRE about situations in which they might be compelled to disclose their risk status potentially leading to discrimination or stigma. The Advisory Group on Risk Evidence Education for Dementia (AGREEDementia) welcomes all concerned with how best to share and use DRE. Supporting understanding in clinicians, stakeholders, and people with or at risk for dementia and clearly delineating risks, benefits, and gaps in knowledge is vital. This brief overview describes elements that made this group effective as a model for other health conditions where there is interest in unfettered collaboration to discuss diagnostic uncertainty and the appropriate use and communication of health-related risk information.

IntroductionThis study describes practices for disclosing individual research results to participants in Alzheimer's disease research.MethodsAn online survey of clinical core leaders at National Institutes of Health-funded Alzheimer's Disease Research Centers in the United States (response rate: 30/31, 97%) examined return of results practices across nine different types of research results.ResultsMost centers had returned consensus research diagnoses (83%) and neuropsychological test results (73%), with fewer having shared amyloid positron emission tomography (43%), tau imaging (10%), or apolipoprotein E (APOE) genotype (7%) results. Centers reported having disclosed a mean of 3.1 types of results (standard deviation = 2.1; range 0-8). The most commonly cited reason for disclosure was to inform participants' medical decision-making (88%). Disclosure involved multiple professionals and modalities, with neurologists (87%) and in-person visits (85%) most commonplace.DiscussionCenters varied widely as to whether and how they disclosed research results. Diagnostic and cognitive test results were more commonly returned than genetic or biomarker results.

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Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Background and hypothesis It remains unclear whether the relation of chronic kidney disease (CKD) with cognitive dysfunction is independent of blood pressure (BP). We evaluated kidney function in relation to premorbid BP measurements, cerebral small vessel disease (CSVD), and incident mild cognitive impairment (MCI) and dementia in Framingham Offspring Cohort participants. Methods We included Framingham Offspring participants free of dementia, attending an examination during midlife (exam cycle 6, baseline) for ascertainment of kidney function status, with brain magnetic resonance imaging late in life (exam cycles 7–9), cognitive outcome data, and available interim hypertension and BP assessments. We related CKD (estimated glomerular filtration rate <60 ml/min/1.73 m2) and albuminuria (urine albumin-to-creatinine ratio ≥30 mg/g) to CSVD markers and cognitive outcomes using multivariable regression analyses. Results Among 2604 participants (mean age 67.4 ± 9.2, 64% women, 7% had CKD, and 9% albuminuria), albuminuria was independently associated with covert infarcts [adjusted OR, 1.55 (1.00–2.38); P  = 0.049] and incident MCI and dementia [adjusted hazard ratio (HR), 1.68 (1.18–2.41); P  = 0.005 and 1.71, (1.11–2.64); P  = 0.015, respectively]. CKD was not associated with CSVD markers but was associated with a higher risk of incident dementia [HR, 1.53 (1.02–2.29); P  = 0.041]. While albuminuria was predictive of the Alzheimer's disease subtype [adjusted HR = 1.68, (1.03–2.74); P  = 0.04), CKD was predictive of vascular dementia [adjusted HR, 2.78 (1.16–6.68); P  = 0.023]. Conclusions Kidney disease was associated with CSVD and cognitive disorders in asymptomatic community dwelling participants. The relation was independent of premorbid BP, suggesting that the link between kidney and brain disease may involve additional mechanisms beyond BP-related injury. [ABSTRACT FROM AUTHOR]

Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions. Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).

IntroductionGenetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood.MethodsWe conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset.ResultsGenome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)-based tests (P

BackgroundWith the onset of prevention trials for individuals at high risk for Alzheimer disease, there is increasing need for accurate risk prediction to inform study design and enrollment, but available risk estimates are limited. We developed risk estimates for the incidence of mild cognitive impairment (MCI) or dementia among cognitively unimpaired individuals by APOE-e4 dose for the genetic disclosure process of the Alzheimer's Prevention Initiative Generation Study, a prevention trial in cognitively unimpaired APOE-e4/e4 homozygote individuals.Methods and findingsWe included cognitively unimpaired individuals aged 60-75 y, consistent with Generation Study eligibility criteria, from the National Alzheimer's Coordinating Center (NACC) (n = 5,073, 158 APOE-e4/e4), the Rotterdam Study (n = 6,399, 156 APOE-e4/e4), the Framingham Heart Study (n = 4,078, 67 APOE-e4/e4), and the Sacramento Area Latino Study on Aging (SALSA) (n = 1,294, 11 APOE-e4/e4). We computed stratified cumulative incidence curves by age (60-64, 65-69, 70-75 y) and APOE-e4 dose, adjusting for the competing risk of mortality, and determined risk of MCI and/or dementia by genotype and baseline age. We also used subdistribution hazard regression to model relative hazard based on age, APOE genotype, sex, education, family history of dementia, vascular risk, subjective memory concerns, and baseline cognitive performance. The four cohorts varied considerably in age, education, ethnicity/race, and APOE-e4 allele frequency. Overall, cumulative incidence was uniformly higher in NACC than in the population-based cohorts. Among APOE-e4/e4 individuals, 5-y cumulative incidence was as follows: in the 60-64-y age stratum, it ranged from 0% to 5.88% in the three population-based cohorts versus 23.06% in NACC; in the 65-69-y age stratum, from 9.42% to 10.39% versus 34.62%; and in the 70-75-y age stratum, from 18.64% to 33.33% versus 38.34%. Five-year incidence of dementia was negligible except for APOE-e4/e4 individuals and those over 70 y. Lifetime incidence (to age 80-85 y) of MCI or dementia for the APOE-e4/e4 individuals in the long-term Framingham and Rotterdam cohorts was 34.69%-38.45% at age 60-64 y, 30.76%-40.26% at 65-69 y, and 33.3%-35.17% at 70-75 y. Confidence limits for these estimates are often wide, particularly for APOE-e4/e4 individuals and for the dementia outcome at 5 y. In regression models, APOE-e4 dose and age both consistently increased risk, as did lower education, subjective memory concerns, poorer baseline cognitive performance, and family history of dementia. We discuss several limitations of the study, including the small numbers of APOE-e4/e4 individuals, missing data and differential dropout, limited ethnic and racial diversity, and differences in definitions of exposure and outcome variables.ConclusionsEstimates of the absolute risk of MCI or dementia, particularly over short time intervals, are sensitive to sampling and a variety of methodological factors. Nonetheless, such estimates were fairly consistent across the population-based cohorts, and lower than those from a convenience cohort and those estimated in prior studies-with implications for informed consent and design for clinical trials targeting high-risk individuals.

The association between cardiometabolic risk factors and cognitive function has been well documented, but the underlying mechanisms are not fully understood. This longitudinal study aimed to investigate the potential mediating role of DNA methylation in this association. We conducted the analyses in 3 708 participants (mean [standard deviation { SD }] age: 67.3 [9.5], women: 57.9%) from the Health and Retirement Study who were assessed in the 2014–2020 waves, had Infinium Methylation EPIC BeadChip methylation assays from the 2016 Venous Blood Study, and had cognitive assessment between 2016 and 2020. Causal mediation analyses were used to test the mediation role of DNA methylation in the associations between cardiometabolic risk factors and cognition, adjusting for demographic, socioeconomic, and lifestyle factors. Hypertension (−0.061 in composite cognitive z -score; 95% confidence interval [CI: −0.119, −0.004]) and diabetes (−0.134; 95% CI: [−0.198, −0.071]) were significantly associated with worse cognitive function while abnormal body weight and hypercholesterolemia were not. An increased number of cardiometabolic risk factors was associated with worse cognitive function (p  = .002). DNA methylation significantly mediated the association of hypertension (mediated effect on composite cognitive z -score: −0.023; 95% CI: −0.033, −0.014), diabetes (−0.022; 95% CI: −0.032, −0.014), and obesity (−0.021; 95% CI: −0.033, −0.011) with cognitive function, whereas the mediation effect was not observed for having hypercholesterolemia. The estimated proportions mediated were 37.4% for hypertension and 16.7% for diabetes. DNA methylation may be an important mediator linking cardiometabolic risk factors to worse cognition and might even provide a potential target for dementia prevention. [ABSTRACT FROM AUTHOR]

ObjectiveTo identify a causative variant(s) that may contribute to Alzheimer disease (AD) in African Americans (AA) in the ATP-binding cassette, subfamily A (ABC1), member 7 (ABCA7) gene, a known risk factor for late-onset AD.MethodsCustom capture sequencing was performed on ∼150 kb encompassing ABCA7 in 40 AA cases and 37 AA controls carrying the AA risk allele (rs115550680). Association testing was performed for an ABCA7 deletion identified in large AA data sets (discovery n = 1,068; replication n = 1,749) and whole exome sequencing of Caribbean Hispanic (CH) AD families.ResultsA 44-base pair deletion (rs142076058) was identified in all 77 risk genotype carriers, which shows that the deletion is in high linkage disequilibrium with the risk allele. The deletion was assessed in a large data set (531 cases and 527 controls) and, after adjustments for age, sex, and APOE status, was significantly associated with disease (p = 0.0002, odds ratio [OR] = 2.13 [95% confidence interval (CI): 1.42-3.20]). An independent data set replicated the association (447 cases and 880 controls, p = 0.0117, OR = 1.65 [95% CI: 1.12-2.44]), and joint analysis increased the significance (p = 1.414 × 10(-5), OR = 1.81 [95% CI: 1.38-2.37]). The deletion is common in AA cases (15.2%) and AA controls (9.74%), but in only 0.12% of our non-Hispanic white cohort. Whole exome sequencing of multiplex, CH families identified the deletion cosegregating with disease in a large sibship. The deleted allele produces a stable, detectable RNA strand and is predicted to result in a frameshift mutation (p.Arg578Alafs) that could interfere with protein function.ConclusionsThis common ABCA7 deletion could represent an ethnic-specific pathogenic alteration in AD.

Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

Neurocognitive disorders--including delirium, mild cognitive impairment and dementia--are characterized by decline from a previously attained level of cognitive functioning. These disorders have diverse clinical characteristics and aetiologies, with Alzheimer disease, cerebrovascular disease, Lewy body disease, frontotemporal degeneration, traumatic brain injury, infections, and alcohol abuse representing common causes. This diversity is reflected by the variety of approaches to classifying these disorders, with separate groups determining criteria for each disorder on the basis of aetiology. As a result, there is now an array of terms to describe cognitive syndromes, various definitions for the same syndrome, and often multiple criteria to determine a specific aetiology. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides a common framework for the diagnosis of neurocognitive disorders, first by describing the main cognitive syndromes, and then defining criteria to delineate specific aetiological subtypes of mild and major neurocognitive disorders. The DSM-5 approach builds on the expectation that clinicians and research groups will welcome a common language to deal with the neurocognitive disorders. As the use of these criteria becomes more widespread, a common international classification for these disorders could emerge for the first time, thus promoting efficient communication among clinicians and researchers.

BackgroundSeveral sets of diagnostic criteria have been published for vascular dementia since the 1960s. The continuing ambiguity in vascular dementia definition warrants a critical reexamination.MethodsParticipants at a special symposium of the International Society for Vascular Behavioral and Cognitive Disorders (VASCOG) in 2009 critiqued the current criteria. They drafted a proposal for a new set of criteria, later reviewed through multiple drafts by the group, including additional experts and the members of the Neurocognitive Disorders Work Group of the fifth revision of Diagnostic and Statistical Manual (DSM-5) Task Force.ResultsCognitive disorders of vascular etiology are a heterogeneous group of disorders with diverse pathologies and clinical manifestations, discussed broadly under the rubric of vascular cognitive disorders (VCD). The continuum of vascular cognitive impairment is recognized by the categories of Mild Vascular Cognitive Disorder, and Vascular Dementia or Major Vascular Cognitive Disorder. Diagnostic thresholds are defined. Clinical and neuroimaging criteria are proposed for establishing vascular etiology. Subtypes of VCD are described, and the frequent cooccurrence of Alzheimer disease pathology emphasized.ConclusionsThe proposed criteria for VCD provide a coherent approach to the diagnosis of this diverse group of disorders, with a view to stimulating clinical and pathologic validation studies. These criteria can be harmonized with the DSM-5 criteria such that an international consensus on the criteria for VCD may be achieved.

Worldwide, over 35 million people suffer from Alzheimer's disease and related dementias. This number is expected to triple over the next 40 years. How can we improve the evidence supporting strategies to reduce the rate of dementia in future generations? The risk of dementia is likely influenced by modifiable factors such as exercise, cognitive activity, and the clinical management of diabetes and hypertension. However, the quality of evidence is limited and it remains unclear whether specific interventions to reduce these modifiable risk factors can, in turn, reduce the risk of dementia. Although randomized controlled trials are the gold-standard for causality, the majority of evidence for long-term dementia prevention derives from, and will likely continue to derive from, observational studies. Although observational research has some unavoidable limitations, its utility for dementia prevention might be improved by, for example, better distinction between confirmatory and exploratory research, higher reporting standards, investment in effectiveness research enabled by increased data-pooling, and standardized exposure and outcome measures. Informed decision-making by the general public on low-risk health choices that could have broad potential benefits could be enabled by internet-based tools and decision-aids to communicate the evidence, its quality, and the estimated magnitude of effect.

BackgroundStudies that have investigated the association between markers of inflammation and risk of dementia are conflicting. Therefore, the researchers conducted a systematic review and meta-analysis of observational studies with the hypothesis that an increased level of peripheral proinflammatory markers would be associated with risk of all-cause dementia or Alzheimer's disease (AD).MethodsThe researchers conducted a literature search of observational studies indexed in the PubMed and PsycInfo databases. Selected studies included those with at least one peripheral inflammatory biomarker and its association with risk of all-cause dementia or AD. Random effects models were used to generate pooled hazard ratios (HRs) comparing the top versus bottom quantile of inflammatory marker level. Heterogeneity was assessed using the I (2) statistic.ResultsSeven studies were identified, combining for a total 5,717 participants, 746 cases of all-cause dementia and 565 cases of AD. An increased level of C-reactive protein was associated with a 45% increased risk of all-cause dementia (HR: 1.45; 95% CI: 1.10, 1.91). Similarly, a higher level of interleukin-6 was associated with a 32% increased risk (HR: 1.32; 95% CI: 1.06, 1.64) of all-cause dementia. For AD alone, the association with C-reactive protein was less pronounced (HR: 1.21; 95% CI: 1.03, 1.42) and interleukin-6 was not associated with risk of AD (HR: 1.06; 95% CI: 0.83, 1.35). No significant heterogeneity was found in any of the meta-analyses (I (2) = 0%-40%, p ≥ .16).ConclusionsAn increased peripheral level of inflammatory markers is associated with a modest increase in risk of all-cause dementia. Evidence for an association with risk of AD alone is limited.

ObjectiveRecent genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) identified 9 novel risk loci. Discovery of functional variants within genes at these loci is required to confirm their role in Alzheimer disease (AD). Single nucleotide polymorphisms that influence gene expression (eSNPs) constitute an important class of functional variants. We therefore investigated the influence of the novel LOAD risk loci on human brain gene expression.MethodsWe measured gene expression levels in the cerebellum and temporal cortex of autopsied AD subjects and those with other brain pathologies (∼400 total subjects). To determine whether any of the novel LOAD risk variants are eSNPs, we tested their cis-association with expression of 6 nearby LOAD candidate genes detectable in human brain (ABCA7, BIN1, CLU, MS4A4A, MS4A6A, PICALM) and an additional 13 genes ±100 kb of these SNPs. To identify additional eSNPs that influence brain gene expression levels of the novel candidate LOAD genes, we identified SNPs ±100 kb of their location and tested for cis-associations.ResultsCLU rs11136000 (p = 7.81 × 10(-4)) and MS4A4A rs2304933/rs2304935 (p = 1.48 × 10(-4)-1.86 × 10(-4)) significantly influence temporal cortex expression levels of these genes. The LOAD-protective CLU and risky MS4A4A locus alleles associate with higher brain levels of these genes. There are other cis-variants that significantly influence brain expression of CLU and ABCA7 (p = 4.01 × 10(-5)-9.09 × 10(-9)), some of which also associate with AD risk (p = 2.64 × 10(-2)-6.25 × 10(-5)).ConclusionsCLU and MS4A4A eSNPs may at least partly explain the LOAD risk association at these loci. CLU and ABCA7 may harbor additional strong eSNPs. These results have implications in the search for functional variants at the novel LOAD risk loci.