The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.
Characterizing Performance Gaps of a Code-Based Dementia Algorithm in a Population-Based Cohort of Cognitive Aging
Background: Multiple algorithms with variable performance have been developed to identify dementia using combinations of billing codes and medication data that are widely available from electronic health records (EHR). If the characteristics of misclassified patients are clearly identified, modifying existing algorithms to improve performance may be possible. Objective: To examine the performance of a code-based algorithm to identify dementia cases in the population-based Mayo Clinic Study of Aging (MCSA) where dementia diagnosis (i.e., reference standard) is actively assessed through routine follow-up and describe the characteristics of persons incorrectly categorized. Methods: There were 5,316 participants (age at baseline (mean (SD)): 73.3 (9.68) years; 50.7% male) without dementia at baseline and available EHR data. ICD-9/10 codes and prescription medications for dementia were extracted between baseline and one year after an MCSA dementia diagnosis or last follow-up. Fisher’s exact or Kruskal-Wallis tests were used to compare characteristics between groups. Results: Algorithm sensitivity and specificity were 0.70 (95% CI: 0.67, 0.74) and 0.95 (95% CI: 0.95, 0.96). False positives (i.e., participants falsely diagnosed with dementia by the algorithm) were older, with higher Charlson comorbidity index, more likely to have mild cognitive impairment (MCI), and longer follow-up (versus true negatives). False negatives (versus true positives) were older, more likely to have MCI, or have more functional limitations. Conclusions: We observed a moderate-high performance of the code-based diagnosis method against the population-based MCSA reference standard dementia diagnosis. Older participants and those with MCI at baseline were more likely to be misclassified.
Cognitive Performance, Sociodemographic Factors, Pure-Tone Audiometry, and their Association with Speech Discrimination: A Prospective Population-Based Study of 1,061 Older Adults
Objective Hearing loss is increasingly recognized as a chronic disease state with important health sequelae. Although considered a central component of routine audiometric testing, the degree to which various patient factors influence speech discrimination is poorly characterized to date. The primary objective of the current work was to describe associations of cognitive performance, sociodemographic factors, and pure-tone audiometry with speech discrimination in older adults. Study Design Prospective study. Setting Olmsted County, Minnesota. Patients There were 1,061 study participants 50 years or older at enrollment in the population-based Mayo Clinic Study of Aging between November 2004 and December 2019 who underwent formal audiometric and cognitive testing included in the current investigation. Main Outcome Measures The primary outcome measure was word recognition scores (WRSs; measured as <100% vs 100% as well as continuous), with pure-tone averages (PTAs; 0.5, 1, 2, and 3 kHz), age, sex, years of education, state area deprivation index (ADI) quintiles, and global cognition z scores as explanatory features. Results The mean (SD) age among the 1,061 participants was 76 (9) years with 528 (50%) males. Participant age [OR (95% CI) for a 10-year increase of 1.8 (1.4–2.3), p < 0.001], male sex [OR = 2.6 (1.9–3.7), p < 0.001], and PTA [OR for a 10-dB hearing loss increase of 2.4 (2.1–2.8), p < 0.001] were all significantly associated with <100% WRSs, with the greatest explanatory ability attributable to the PTA. Years of education (p = 0.9), state ADI quintile (p = 0.6), and global cognitive performance (p = 0.2) were not associated with WRS. The multivariable model demonstrated strong predictive ability for less than perfect WRSs, with a c index of 0.854. Similar results were seen for WRSs analyzed as continuous, with the multivariable model resulting in an R 2 value of 0.433. Conclusions Although PTA exhibited the greatest influence on speech discrimination, advancing age and male sex both independently increased the likelihood of having worse speech discrimination among older adults, even after accounting for years of education, neighborhood-level socioeconomic disadvantage, and cognitive function. These findings help identify patient factors that can be instrumental when designing screening programs for adult-onset hearing loss.
Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging
AbstractINTRODUCTIONWe examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults.METHODSCross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment.RESULTSP‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p < 0.001), p‐tau217 (OR 1.70, 95% CI 1.10–2.61, p = 0.016), and t‐tau (OR 1.44, 95% CI 1.08–1.92, p = 0.012) were associated with appetite change. We also found that p‐tau181 and p‐tau217 were associated with increased symptoms of agitation (OR 1.93, 95% CI 1.20–3.11, p = 0.007 and OR 2.04, 95% CI 1.21–3.42, p = 0.007, respectively), and disinhibition (OR 2.39, 95% CI 1.45–3.93, p = 0.001 and OR 2.30, 95% CI 1.33–3.98, p = 0.003, respectively). Aβ42/Aβ40 and NfL were not associated with NPS.CONCLUSIONHigher plasma‐derived p‐tau181 and p‐tau217 levels are associated with increased symptoms of appetite change, agitation, and disinhibition. These findings may support the validity of plasma tau biomarkers for predicting behavioral symptoms that often accompany cognitive impairment.HIGHLIGHTS We studied 1005 community‐dwelling persons aged ≥ 50 years Higher plasma tau levels are associated with increased neuropsychiatric symptoms Aβ42/Aβ40 and NfL are not associated with neuropsychiatric symptoms Clinicians should treat neuropsychiatric symptoms in persons with high plasma‐derived tau
Correlation of Blood Metal Concentrations with Cognitive Scores and Neuroimaging Findings in Patients with Total Joint Arthroplasty
Total joint arthroplasty (TJA) implants are composed of metals, ceramics, and/or polyethylene. Studies suggest that the debris released from metal implants may possess neurotoxic properties with reports of neuropsychiatric symptoms and memory deficits, which could be relevant to Alzheimer’s disease and related dementias. This exploratory study examined the cross-sectional correlation of blood metal concentrations with cognitive performance and neuroimaging findings in a convenience sample of 113 TJA patients with history of elevated blood metal concentrations of either titanium, cobalt and/or chromium. Associations with neuroimaging measures were observed but not with cognitive scores. Larger studies with longitudinal follow-up are warranted.
Mortality across the Alzheimer’s disease clinical stages: An analysis using the U.S. National Alzheimer’s Coordinating Center Uniform Data Set
AbstractBackgroundUnderstanding mortality risk across the Alzheimer’s disease (AD) clinical stages is essential for resource planning and estimating the value of disease modifying therapies (DMTs), which may slow progression. Such studies are lacking.MethodThe study used the Uniform Data Set of the National Alzheimer’s Coordinating Center (NACC) from September 1, 2005 to March 1, 2021 to assess mortality risk across the AD clinical stages. It included 12,414 participants aged ≥ 50 years, who contributed to the following stages: cognitively unimpaired (CU n = 11,458), incident prodromal AD (n = 937), and AD dementia (n = 745). AD etiology and stage were established based on clinical evaluation and cognitive, behavioral, and functional scores. Study centers report mortality for actively followed participants. Participants contributed observation time until all‐cause death, disease progression, discontinuation, loss to follow‐up, data cutoff or the last visit before a longer than 36‐month gap in visits or recorded scores.Hazard ratios for each AD stage versus CU were estimated using Cox proportional hazards models. Least absolute shrinkage and selection operator facilitated final predictor selection.ResultParticipants’ mean age (SD) at study entry was 71.0 years (SD 9.2) (34.9% males). Participants with incident mild, moderate, and severe AD had increased mortality risk relative to CU after controlling for age, sex, education, apolipoprotein E ε4 genotype status, BMI, and residence type. Relative all‐cause mortality risk by AD stage decreased with increasing age; the HRs (95% CI) for mortality at 65 years of age were 6.7 (2.7‐16.9), 14.8 (8.8‐24.8), and 30.1 (16.7‐56.8) for mild, moderate and severe AD respectively; at 80 years of age, the corresponding HR (95% CI) were 2.4 (1.7‐3.3), 3.1 (2.4‐3.9), and 6.6 (4.8‐9.1). Male sex (HR = 1.75, 95% CI 1.52‐2.04) and residing in an institution (vs. private residence; HR = 3.11, 95% CI 2.28‐4.25) significantly increased relative all‐cause mortality risk.ConclusionRelative all‐cause mortality risk increases with AD severity, and more so at younger ages. Despite data limitations, findings are significant as efforts to delay disease, for instance with DMTs, could not only improve patient and caregiver quality of life and reduce costs, but also extend the lives of patients with AD.NIA/NIH Grant U24 AG072122 funds the NACC database.
Identifying Key Patterns of Social and Structural Determinants of Health and Their Association with Dementia Risk in a Population-Based Study of Cognitive Aging (P1-12.007)
Participant-specific interrogation of population-based data to predict cognitive decline from neuropsychiatric symptoms and neuroimaging biomarkers: A machine learning approach (P12-6.001)