scholarly journals Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS

2021 ◽  
Vol 83 (4) ◽  
pp. 1803-1813
Author(s):  
Emily M. Briceño ◽  
Alden L. Gross ◽  
Bruno J. Giordani ◽  
Jennifer J. Manly ◽  
Rebecca F. Gottesman ◽  
...  
Keyword(s):  
Cardiovascular Health ◽  
Data Augmentation ◽  
Meta Analysis ◽  
Data Interpretation ◽  
Health Study ◽  
Cardiovascular Health Study ◽  
Sociocultural Factors ◽  
Meta Analyses ◽  
Cognitive Data ◽  
Score Distributions

Background: Meta-analyses of individuals’ cognitive data are increasing to investigate the biomedical, lifestyle, and sociocultural factors that influence cognitive decline and dementia risk. Pre-statistical harmonization of cognitive instruments is a critical methodological step for accurate cognitive data harmonization, yet specific approaches for this process are unclear. Objective: To describe pre-statistical harmonization of cognitive instruments for an individual-level meta-analysis in the blood pressure and cognition (BP COG) study. Methods: We identified cognitive instruments from six cohorts (the Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Coronary Artery Risk Development in Young Adults study, Framingham Offspring Study, Multi-Ethnic Study of Atherosclerosis, and Northern Manhattan Study) and conducted an extensive review of each item’s administration and scoring procedures, and score distributions. Results: We included 153 cognitive instrument items from 34 instruments across the six cohorts. Of these items, 42%were common across ≥2 cohorts. 86%of common items showed differences across cohorts. We found administration, scoring, and coding differences for seemingly equivalent items. These differences corresponded to variability across cohorts in score distributions and ranges. We performed data augmentation to adjust for differences. Conclusion: Cross-cohort administration, scoring, and procedural differences for cognitive instruments are frequent and need to be assessed to address potential impact on meta-analyses and cognitive data interpretation. Detecting and accounting for these differences is critical for accurate attributions of cognitive health across cohort studies.

scholarly journals Association of CD14 with incident dementia and markers of brain aging and injury

Neurology ◽  
2019 ◽  
Vol 94 (3) ◽  
pp. e254-e266 ◽  
Author(s):  
Matthew P. Pase ◽  
Jayandra J. Himali ◽  
Alexa S. Beiser ◽  
Charles DeCarli ◽  
Emer R. McGrath ◽  
...  
Keyword(s):  
Brain Atrophy ◽  
Cardiovascular Health ◽  
Brain Aging ◽  
Inflammatory Marker ◽  
Meta Analysis ◽  
Health Study ◽  
Cardiovascular Health Study ◽  
Community Based ◽  
Brain Volumes ◽  
Incident Dementia

ObjectiveTo test the hypothesis that the inflammatory marker plasma soluble CD14 (sCD14) associates with incident dementia and related endophenotypes in 2 community-based cohorts.MethodsOur samples included the prospective community-based Framingham Heart Study (FHS) and Cardiovascular Health Study (CHS) cohorts. Plasma sCD14 was measured at baseline and related to the incidence of dementia, domains of cognitive function, and MRI-defined brain volumes. Follow-up for dementia occurred over a mean of 10 years (SD 4) in the FHS and a mean of 6 years (SD 3) in the CHS.ResultsWe studied 1,588 participants from the FHS (mean age 69 ± 6 years, 47% male, 131 incident events) and 3,129 participants from the CHS (mean age 72 ± 5 years, 41% male, 724 incident events) for the risk of incident dementia. Meta-analysis across the 2 cohorts showed that each SD unit increase in sCD14 was associated with a 12% increase in the risk of incident dementia (95% confidence interval 1.03–1.23; p = 0.01) following adjustments for age, sex, APOE ε4 status, and vascular risk factors. Higher levels of sCD14 were associated with various cognitive and MRI markers of accelerated brain aging in both cohorts and with a greater progression of brain atrophy and a decline in executive function in the FHS.ConclusionsCD14 is an inflammatory marker related to brain atrophy, cognitive decline, and incident dementia.

scholarly journals Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American-specific associations

SLEEP ◽  
2019 ◽  
Vol 42 (8) ◽  
Author(s):  
Richard Barfield ◽  
Heming Wang ◽  
Yongmei Liu ◽  
Jennifer A Brody ◽  
Brenton Swenson ◽  
...  
Keyword(s):  
Daytime Sleepiness ◽  
Cardiovascular Health ◽  
Association Studies ◽  
Meta Analysis ◽  
Health Study ◽  
Cardiovascular Health Study ◽  
P Value ◽  
Uk Biobank ◽  
Ethnic Study ◽  
The Uk

AbstractStudy ObjectivesDaytime sleepiness is a consequence of inadequate sleep, sleep–wake control disorder, or other medical conditions. Population variability in prevalence of daytime sleepiness is likely due to genetic and biological factors as well as social and environmental influences. DNA methylation (DNAm) potentially influences multiple health outcomes. Here, we explored the association between DNAm and daytime sleepiness quantified by the Epworth Sleepiness Scale (ESS).MethodsWe performed multi-ethnic and ethnic-specific epigenome-wide association studies for DNAm and ESS in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 619) and the Cardiovascular Health Study (n = 483), with cross-study replication and meta-analysis. Genetic variants near ESS-associated DNAm were analyzed for methylation quantitative trait loci and followed with replication of genotype-sleepiness associations in the UK Biobank.ResultsIn MESA only, we detected four DNAm-ESS associations: one across all race/ethnic groups; three in African-Americans (AA) only. Two of the MESA AA associations, in genes KCTD5 and RXRA, nominally replicated in CHS (p-value < 0.05). In the AA meta-analysis, we detected 14 DNAm-ESS associations (FDR q-value < 0.05, top association p-value = 4.26 × 10−8). Three DNAm sites mapped to genes (CPLX3, GFAP, and C7orf50) with biological relevance. We also found evidence for associations with DNAm sites in RAI1, a gene associated with sleep and circadian phenotypes. UK Biobank follow-up analyses detected SNPs in RAI1, RXRA, and CPLX3 with nominal sleepiness associations.ConclusionsWe identified methylation sites in multiple genes possibly implicated in daytime sleepiness. Most significant DNAm-ESS associations were specific to AA. Future work is needed to identify mechanisms driving ancestry-specific methylation effects.

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