Association of 3.0-T brain magnetic resonance imaging biomarkers with cognitive function in the dallas heart study

IMPORTANCE Understanding the relationships between age-related changes in brain structure and cognitive function has been limited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnically homogeneous cohorts with biased selection based on risk factors. These limitations have prevented the generalizability of results from brain morphology studies. OBJECTIVE To determine the association of 3.0-T structural brain magnetic resonance (MR) imaging measurements with cognitive function in the multiracial/multiethnic, population-based Dallas Heart Study. DESIGN, SETTING, AND PARTICIPANTS Whole-brain, 2-dimensional, fluid-attenuated inversion recovery and 3-dimensional, magnetization-prepared, rapid acquisition with gradient echoMR imaging at 3.0 Twas performed in 1645 Dallas Heart Study participants (mean [SD] age, 49.9 [10.5] years; age range, 19-85 years) who received both brainMRimaging and cognitive screening with the Montreal Cognitive Assessment between September 18, 2007, and December 28, 2009. Measurementswere obtained for white matter hyperintensity volume, total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume. Linear regression and a best predictive modelwere developed to determine the association ofMRimaging biomarkers with the Montreal Cognitive Assessment total score and domain-specific questions. MAIN OUTCOMES AND MEASURES High-resolution anatomical MR imagingwas used to quantify brain volumes. Scores on the screening Montreal Cognitive Assessment were used for cognitive assessment in participants. RESULTS After adjustment for demographic variables, total brain volume (P <.0001, standardized estimate [SE] =.1069), gray matter volume (P <.0001, SE =.1156), white matter volume (P =.008, SE =.0687), cerebrospinal fluid volume (P =.012, SE =-.0667), and hippocampal volume (P <.0001)were significantly associated with cognitive performance. A best predictive model identified gray matter volume (P <.001, SE =.0021), cerebrospinal fluid volume (P =.01, SE =.0024), and hippocampal volume (P =.004, SE =.1017) as 3 brainMR imaging biomarkers significantly associated with the Montreal Cognitive Assessment total score. Questions specific to the visuospatial domainwere associated with the most brainMRimaging biomarkers (total brain volume, gray matter volume, white matter volume, cerebrospinal fluid volume, and hippocampal volume), while questions specific to the orientation domainwere associated with the least brainMRimaging biomarkers (only hippocampal volume). CONCLUSIONS AND RELEVANCE Brain MR imaging volumes, including total brain volume, gray matter volume, cerebrospinal fluid volume, and hippocampal volume, were independently associated with cognitive function and may be important early biomarkers of risk for cognitive insult in a young multiracial/multiethnic population. A best predictive model indicated that a combination of multiple neuroimaging biomarkers may be more effective than a single brain MR imaging volume measurement.