Thyagarajan, Bharat

Abstract Background The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) randomized trial ( n = 977;ClinicalTrials.gov:NCT03243422) demonstrated that hearing intervention slowed 3‐year cognitive decline by 48% among a subgroup of participants. To further investigate differences by treatment with respect to cognitive benefit, we tested the hypothesis that hearing intervention is associated with improved neurodegeneration blood biomarkers 3‐years post‐randomization and assessed whether combining biomarkers and cognitive results improved power in the trial design. Method The ACHIEVE study is a multicenter, parallel‐arm, randomized trial (hearing intervention vs health education control) on 3‐year cognitive decline among adults 70–84years with untreated hearing loss and without substantial cognitive impairment. Participants were recruited from two populations: (1) a long‐standing cardiovascular health observational study (Atherosclerosis Risk in Communities [ARIC]), and (2) de novo community volunteers. Plasma was collected in year 3 in a subsample ( n = 540) while ARIC participants ( n = 164) also had baseline plasma. Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) neurodegenerative biomarkers were derived using the Alamar CNS protein panel. Regression models estimated the association of treatment with 3‐year biomarkers and global cognitive differences in the combined sample and by recruitment source and annualized change from baseline in the ARIC sample. We included a simple composite score of the standardized outcomes (Table 2). Result Among the subsample, baseline characteristics were balanced by treatment. There were no significant differences on 3‐year neurodegeneration biomarker levels by treatment in the combined (Table 1) or de novo groups (Table 2). Among ARIC participants, intervention resulted in lower 3‐year GFAP (mean:‐0.415;95%CI:‐0.712,‐0.118) and NfL (mean:‐0.349;95%CI:‐0.652,‐0.046) (Table 2). Annualized change from baseline analyses among ARIC participants (Table 3) revealed intervention was associated with a slower rate of cognitive decline (difference‐in‐means:0.059;95%CI:0.018,0.100) and a slower rate of increase in GFAP (difference‐in‐means: ‐0.060;95%CI:‐0.112,‐0.009). Differences in estimates suggest combined score, relative to cognition alone, may increase power in clinical trials that show a positive effect (ARIC subgroup: p = 0.02vs. 0.08[Table 2] and p = 0.0009vs.0.048[Table 3]). Conclusion Hearing intervention was associated with positive 3‐year effects on neurodegeneration blood biomarkers in ARIC participants which parallels cognitive decline results. Results provides objective evidence of brain changes following hearing intervention and potential signal of a more powerful combined outcome approach for future brain health clinical trials.

Introduction: Physical activity (PA) has been identified as a protective factor for dementia, but the mechanisms linking PA to brain health are unclear. To elucidate potential pathways linking PA to brain health, we tested the hypothesis that higher levels of late-life PA are associated with a lower burden of Alzheimer’s disease (AD) pathology, cerebrovascular disease, and neurodegeneration measured through brain imaging and plasma biomarkers. Methods: ARIC-NCS participants without dementia in 2011-13 and with measures of PA, 3T brain magnetic resonance imaging (MRI), and stored plasma samples were examined (n=1,771; mean age: 76.5 years; 40.5% male; 27.6% Black). Participants were classified as meeting or not meeting 2018 aerobic PA guidelines based on a standardized interviewer-administered questionnaire. MRI biomarkers included white matter hyperintensity (WMH) volume (cm 3 ), total brain volume (TBV) (cm 3 ), and cortical thickness (CT) (mm). Plasma biomarkers of the ratio of amyloid beta 42 to 40 (Aβ42/Aβ40), phosphorylated Tau-181 (p-Tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured using Quanterix Simoa immunoassays. All biomarkers were standardized to measures in 2011-13 to facilitate comparisons. Covariate-adjusted linear regression models estimated cross-sectional associations of PA with MRI or plasma biomarkers. Covariate-adjusted linear mixed effects models quantified associations of PA with the 5-year rate of change in a subset of participants with MRI (n=669) or plasma (n=651) biomarkers at both baseline and follow-up from 2011-19 (median follow-up: 5.4 years). Results: Meeting versus not meeting aerobic PA guidelines was cross-sectionally associated with lower volumes of WMH (β = -0.16, 95% CI: -0.25, -0.07), higher TBV (β = 0.09; 95% CI: 0.05, 0.13), and lower plasma NfL (β = -0.102, 95% CI: -0.184, -0.021) ( Figure ). Late-life PA was not associated with 5-year rates of change in MRI or plasma biomarkers. Conclusions: Late-life PA was cross-sectionally associated with less neurodegeneration and cerebrovascular disease. Associations with 5-year changes in imaging and plasma biomarkers of AD pathology, cerebrovascular disease, or neurodegeneration were not statistically supported. Longitudinal biomarker studies with wearable devices that quantify other daily intensity-based movement metrics (e.g., light PA) and larger sample sizes are needed to further examine mechanisms linking PA to brain health.

Background: Thrombo-inflammation is a hallmark of acute Covid-19, with higher thrombo-inflammatory markers during infection associated with adverse outcomes. We hypothesized that higher pre-pandemic biomarkers, reflecting a higher thrombo-inflammatory setpoint, might identify people at greater risk of severe manifestations of Covid-19. Hypothesis: Pre-pandemic inflammation markers are associated with risk of hospitalized or fatal (hereafter, “severe”) Covid-19 in a multi-ethnic US sample. Methods: From 2020-2023, C4R harmonized pre-pandemic measures and ascertained Covid-19 across 14 longstanding cohort studies. In 12 cohorts, we assessed biomarker data and covariates from the study visit closest to the pandemic for 6 analytes shown in the Table. HRs of severe Covid-19 by pre-pandemic biomarkers were estimated using cause-specific Cox regression, treating non-severe Covid-19 as a competing risk, and adjusting for pre-pandemic sociodemographic and clinical characteristics. Results: Biomarkers were measured a mean of 20 years before the pandemic with different sample sizes for each (Table footnote). Mean age at the start of the pandemic was in the 60s or 70s depending on the biomarker. The most represented race or ethnic groups were White and Black. The largest sample was for C-reactive protein, and there were 1,001 severe Covid-19 cases among 38,784 participants. In the adjusted models, considered individually, higher CRP, leukocyte count, factor VIII and fibrinogen, but not other markers, were associated with greater risk of severe Covid-19 (Table).Associations were robust across subgroups and time since biomarker measurement (example for C-reactive protein in Figure). Conclusions: In this prospective multi-study analysis of a multi-ethnic population, higher basal levels of thrombo-inflammation markers were associated with greater risk of severe Covid-19. Since we considered non-severe Covid-19 as a competing risk, associations may reflect factors related to progression to more serious Covid-19 illness.

AbstractBackgroundBlood‐based biomarkers show promise as a noninvasive, inexpensive method for measuring Alzheimer’s disease pathology throughout the lifecourse. However, the predictive and classification accuracy of these biomarkers at different stages of the lifecourse and among diverse, community‐dwelling populations requires further investigation.MethodBetween 2014 and 2015, 329 dementia‐free participants from the Atherosclerosis Risk in Communities Study underwent brain magnetic resonance imaging (MRI) and florbetapir positron emission tomography (PET). Amyloid positivity was defined as a global cortex standardized uptake value ratio greater than 1.2. Stored plasma samples collected in midlife (1993‐95, mean age 58.5 years) and late‐life (2011‐13, mean age 76.2 years) from a subsample of 259 participants were assayed in 2022 using Quanterix SiMoA. The assay quantified amyloid‐β (Aβ)42/40, phosphorylated tau at threonine 181 (p‐Tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Unadjusted and covariate‐adjusted logistic regression models estimated the association between plasma biomarkers from midlife and late‐life and amyloid positivity in late‐life. Unadjusted receiver operating characteristic curves documented the classification accuracy of the plasma biomarkers separately and collectively.ResultThe sample (Table 1) included 151 women (58.1%), 105 Black participants (40.4%), and 136 (52.3%) participants with amyloid positivity. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, assays measured in midlife were not associated with amyloid positivity in late‐life (Table 2). However, late‐life measurements of Aβ42/40, p‐Tau181, and GFAP and change per decade from midlife to late‐life in p‐Tau181 and GFAP were associated with greater odds of amyloid positivity. The greatest classification accuracy (Figure 1) was achieved by using all assays measured in midlife and late‐life (AUC = 0.754), although the accuracy when using only late‐life measures was comparable (AUC = 0.737).ConclusionLate‐life plasma biomarkers of Alzheimer's disease neuropathology and astrogliosis were associated with late‐life amyloid positivity, but midlife plasma biomarkers obtained 16 to 20 years earlier did not exhibit a statistically significant association. Additional longitudinal research is needed to determine whether changes in plasma biomarkers measured before an individual is classified as amyloid positive can be used to identify individuals at risk of developing Alzheimer's disease.

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50–75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches.

Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 ( APOE ε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers’ association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross‐sectional and prospective association analyses of blood‐derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole‐genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1‐SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04–1.12; P <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; P =0.11) or in the reverse direction (β=−0.012; P =0.076). Additional bidirectional Mendelian randomization analyses revealed that low‐density lipoprotein cholesterol had a causal effect on mtDNA CN (β=−0.084; P <0.001), but the reverse direction was not significant ( P =0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low‐density lipoprotein cholesterol level ( P =0.52), whereas there was a strong direct causal effect of higher low‐density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=−0.092; P <0.001). Conclusions Our findings indicate that high low‐density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

AbstractBACKGROUNDSoluble intercellular adhesion molecule 1 (sICAM-1) is associated with endothelial dysfunction and clinical cardiovascular disease. We investigated the relationship of subclinical atherosclerosis with sICAM-1 concentration.METHODSsICAM-1 concentration was assayed at year 15 of the Coronary Artery Risk Development in Young Adults (CARDIA) Study (black and white men and women, average age 40 years). We assessed progression of coronary artery calcification (CAC) through year 20 (n = 2378), and both carotid artery stenosis (n = 2432) and intima-media thickness (IMT) at year 20 (n = 2240).RESULTSMedian sICAM-1 was 145.9 μg/L. Among a subgroup with advanced atherosclerotic plaque (either CAC or stenosis), IMT was 0.010 (95% CI 0.003–0.017 mm) higher per SD of sICAM-1 (44 μg/L) in a model adjusted for age, race, sex, clinic, smoking, exercise, body size, education, blood pressure, antihypertensive medication, plasma lipids, and cholesterol-lowering medication. With the same adjustment, the odds ratio (OR) for the presence of year-20 carotid artery stenosis per SD of sICAM-1 was 1.12 (95% CI 1.01–1.25, P &lt; 0.04), whereas for occurrence of CAC progression the OR was 1.16 (1.04–1.31, P &lt; 0.01). The associations with CAC and carotid stenosis were strongest in the top 20th of the sICAM-1 distribution.CONCLUSIONSsICAM-1 concentration may be an early biomarker that indicates changes in the artery wall that accompany atherosclerosis, as well as the presence of advanced plaque in the coronary and carotid arteries. This finding holds in people with low total burden of atherosclerosis, decades before the development of clinical CVD.