Processing speed is a fundamental building block of cognition that declines reliably with age. While white matter degradation and connectivity decreases among gray matter regions may be important contributors to age-related declines in speed, cerebrovascular health may (partly) explain some of these variations, especially in older individuals. Therefore, the goals of this study were to examine whether changes in cerebrovascular reactivity (CVR) to CO2 inhalation, a marker of cerebrovascular function, is associated with changes in processing speed. Change in both speed and CVR was measured longitudinally in two waves four years apart. Because cerebrovascular function may impact cognition differentially in younger and older individuals, we studied their association separately in two age groups.

Participants

The data were collectd from a large-scale aging project: the Dallas Lifespan Brain Study. 207 subjects (aged 20-88) participated in Wave-1 with both cognitive and CVR MRI data collected. 116 of these participants returned for Wave-2, and the same cognitive and CVR MRI data were collected again. The interval between the two waves was 4.08+/-0.02 years. MRI experiment CVR measurement was performed on a Philips 3T system, and Wave-1 and Wave-2 studies used identical protocols. Briefly, CVR was assessed using a hypercapnia challenge.¹ The subject breathed a 5% CO2 gas mixture or room air in an interleaved manner, while BOLD images were continuously collected for 7 min. CVR maps were obtained by general linear regression between BOLD signal and end-tidal CO2 time course.¹

Cognitive Assessment

Processing speed was measured by the speed at which subjects judged whether digit strings at three levels of complexity were same or different, and the three scores were combined to form a processing speed construct Other cognitive constructs assessed included working memory, reasoning and episodic memory.

Data analysis

We divided the Wave 1 participants into 2 groups: younger (20-54 y/o) and older. Changes in processing speed and CVR over the four-year interval were each measured by the formula: (Wave1-Wave2)/follow-up interval. For each age group, a linear regression model was developed where after controlling for age, change in CVR was used to predict change in processing speed. All reported effect are significant at P less than 0.05.

Age-related decline in CVR and cognition.

Decade-by-decade CVR brain maps depaicting age-related decreases in CVR are shown in Figure 1a. Figure 1b shows the strong relationship between CVR at Wave 1 versus Wave 2, providing evidence that the two waves showed highly reproducible, age effects. Figure 2 shows the reproducibility across the two waves of age-related decline in processing speed (Figure 2).

Longitudinal relationship between CVR and cognition

65 younger participants and 51 older participants contributed data to both Wave 1 and 2. In the older group, after controlling for age, change in whole-brain CVR predicted change in processing speed with a similar significant relationship found as well for frontal, temporal, occipital and insular regiona (P<0.05): subjects with faster CVR decline tend to have faster decline in processing speed (Figure 3). This relationship was not observed in the young subjects. No other cognitive domains were correlated with CVR changes.

In elderly, but not young individuals, the rate of change in CVR over four years predicted decline in processing speed, indicating that declines in vascular brain health contribute to changes in the information processing speed in older but not young and middle-aged adults. These may be the first longitudinal data showing a direct impact of changes in cerebrovascular health showing a direct relationship to cognitive change.