Elsevier

NeuroImage

Volume 44, Issue 3, 1 February 2009, Pages 647-652
NeuroImage

Caffeine's effects on cerebrovascular reactivity and coupling between cerebral blood flow and oxygen metabolism

https://doi.org/10.1016/j.neuroimage.2008.09.057Get rights and content

Abstract

The blood-oxygenation-level-dependent (BOLD) signal is dependent on multiple physiological factors such as cerebral blood flow (CBF), local oxygen metabolism (CMRO2) and cerebral blood volume (CBV). Since caffeine affects both CBF and neural activity, its effects on BOLD remain controversial. The calibrated BOLD approach is an excellent tool to study caffeine because it combines CBF and BOLD measures to estimate changes in CMRO2. The present study used the calibrated BOLD approach with 5% CO2 to determine if a 2.5 mg/kg intravenous injection of caffeine changes the coupling between CBF and CMRO2 during motor and visual tasks. The results show that caffeine decreases n, the CBF:CMRO2 coupling ratio, from 2.58 to 2.33 in motor (p = 0.006) and from 2.45 to 2.23 in visual (p = 0.002) areas respectively. The current study also demonstrated that caffeine does not alter cerebrovascular reactivity to CO2. These results highlight the importance of the calibrated BOLD approach in improving interpretation of the BOLD signal in the presence of substances like caffeine.

Introduction

Caffeine is a widely used psychostimulant that is present in many foods and drinks, primarily in coffee and tea. According to a recent consumption report, 54% of adults in the United States drink coffee every day, with an average daily consumption of 3.1 cups/person (> 500mg) (Field et al., 2003). Caffeine belongs to the methylxanthine family, which are cerebral vasoconstrictors and systemic vasodilators (Mulderink et al., 2002). It is widely accepted that caffeine's effect on the central nervous system is because it is an antagonist for adenosine receptors, especially types A1 and A2A (Tarter et al., 1998). Since adenosine inhibits the release of excitatory neurotransmitters and affects neuronal firing rate through activation of type A1 receptors, binding of an antagonist such as caffeine leads to increased neural stimulation through disinhibitory mechanism (Koppelstaetter et al., 2008). This is likely the reason why subjects report better performance and higher alertness after ingestion of caffeine. On the other hand, the A2A receptors are responsible for the vasoconstrictive effects of caffeine. Given caffeine's nonspecific binding to both types of receptors, it is capable of altering the coupling between blood flow and neural activity depending on the ratio between the two types of receptors in different areas of the brain (Laurienti et al., 2003).

Blood-oxygenation-level-dependent (BOLD) imaging is a popular method used to measure brain activity through changes in blood oxygenation. However, it is only an indirect measure because BOLD is based on the interaction between many factors, including oxygen consumption and cerebral blood flow (CBF) (Matthews and Jezzard, 2004). In a recent study, Mulderink et al. reported that caffeine increases the BOLD response by 37% and 26% in motor and visual areas respectively, and concluded that caffeine can be used as a BOLD contrast booster (Mulderink et al., 2002). The authors attributed this result to caffeine's ability to decrease CBF, which decreases BOLD baseline, allowing for a larger capacity of BOLD response to activation. However, due to the complexity of BOLD and inter-subject variability in the metabolism of caffeine, caffeine's effect on BOLD remains controversial (Bendlin et al., 2007, Koppelstaetter et al., 2008, Laurienti et al., 2003). Given the worldwide popularity of caffeine, it is imperative to understand how it affects BOLD.

In order to separate the metabolic and vascular components of functional activity, Davis et al. introduced the calibrated BOLD approach (Davis et al., 1998). This approach uses functional ASL to establish a mathematical relationship between CBF, BOLD and cerebral metabolic rate of oxygen (CMRO2):ΔBOLDBOLD0=M(1(CMRO2CMRO2,0)β(CBFCBF0)αβ)where M is the maximum BOLD contrast observable should all deoxyhemoglobin (dHb) be replaced with fully oxygenated blood, and is related to echo time (TE), a proportional constant A which is field-strength and sample-specific, as well as baseline (denoted by subscript 0) cerebral blood volume (CBV) and dHb:M=TEACBV0[dHb]0β

The constant α, also known as Grubb's constant, describes the relationship between CBF and CBV and is assumed to be 0.38 (Grubb et al., 1974). β is a constant that relates BOLD to field strength and oxygenation, and is typically set to 1.5 (Boxerman et al., 1995, Davis et al., 1998, Hoge et al., 1999a, Leontiev and Buxton, 2007). The basic idea of the calibrated BOLD approach is to use a vasoactive agent such as CO2 that has minimal effect on CMRO2 to “calibrate” the BOLD contrast against known CBF levels by estimating M. The estimated M can then be applied to BOLD and CBF changes from functional data to calculate relative changes in CMRO2:CMRO2CMRO2,0=(1(ΔBOLD/BOLD0)M)1/β(CBFCBF0)αβ

The calibrated BOLD approach is an excellent tool for studying the effects of substances such as caffeine on BOLD as it can provide a measurement of the CBF:CMRO2 coupling ratio–n, which is expected to change given the neurostimulative and vasoactive effects of caffeine. In this study, we use the calibrated BOLD approach to examine how caffeine alters CBF:CMRO2 coupling during motor-visual task.

Section snippets

Experimental setup

Fourteen healthy subjects (4 males, 10 females, average age 27 ± 10 years) were recruited in accordance with the university's Institutional Review Board and written informed consent was obtained from every subject. All scans were completed before noon to minimize diurnal and dietary fluctuations. Subjects were asked to abstain from caffeine for 12–24 h prior to each study. A brief questionnaire was used to determine each subject's daily caffeine usage.

Prior to each study, two baseline blood

Results

The physiological parameters averaged over all subjects are listed in Table 1. The differences between pre- and post-caffeine sessions were not statistically significant. Breathing the CO2 enriched gas increased etCO2 by 14.1 mmHg and 12.8 mmHg respectively before and after caffeine injection. This difference was not significant.

Fig. 3 shows the BOLD and CBF timecourses for the hypercapnia scans. The CBF timecourses pre- and post-caffeine appear identical in amplitude and timing

Discussion

There has been much debate on the relationship between baseline perfusion and BOLD due to the complexity of the BOLD signal. The calibrated BOLD approach is an excellent tool for examining how BOLD is coupled to changes in perfusion and neural activity. In the pre-caffeine portion of the study, we used the calibrated BOLD approach to calculate the CBF:CMRO2 coupling ratio in both motor and visual cortices. The M values obtained from the current study (motor: 3.7 ± 1.0, visual: 5.1 ± 2.0) are close

Conclusion

We have demonstrated that the calibrated BOLD approach is a useful method for studying the effects of substances such as caffeine on fMRI. Our findings demonstrate that caffeine does not alter CVR during hypercapnia, but it decreases the CBF:CMRO2 coupling ratio in both motor and visual cortices during task-related activations, potentially through a combination of increased OEF and anaerobic metabolism.

Acknowledgment

This work was supported by NIH grant R01EB002449-03. The authors thank Nancy Crnkovich, Rebecca Ditch and Nondas Leloudas for their assistance with the study.

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    Most studies considered exposures ranging from approximately 100 to 400 mg per day (or exposure/dose period). There were 111 controlled-exposure studies with fixed dose(s) of caffeine administered often via a pill or suspension to subjects, followed by the monitoring of blood pressure changes over the course of a few hours or one day (Addicott et al., 2009; Ammar et al., 2001; Ammon et al., 1983; Arciero et al., 1998, Arciero and Ormsbee, 2009; Astorino et al., 2007; Astorino et al., 2013; Awaad et al., 2011; Bak and Grobbee, 1990, 1991; Barry et al., 2005; Benowitz et al., 1995; Berry et al., 2003; Blaha et al., 2007; Burr et al., 1989; Buscemi et al. 2009, 2010; Cavalcante et al., 2000; Chen and Parrrish, 2009; Childs and de Wit, 2006; Daniels et al., 1998; Del Cosco et al., 2012; Eggertsen et al., 1993; Engels et al., 1999; Farag et al. 2005a, 2005b, 2006, 2010; Fernandez-Elias et al., 2015; Franks et al., 2012; Funatsu et al., 2005; Grasser et al., 2014, 2015; Hamer et al., 2006; Hartley et al., 2000, 2004; Hodgson et al., 1999; Hodgson et al., 2005; Hoffman et al., 2006; Humayun et al., 1997; James, 1994a, 1994b; James and Gregg, 2004; Kaminsky et al., 1998; Karatzis et al., 2005; Kennedy et al., 2008; Kurtz et al., 2013; Lane et al., 1998, 2002; Lemery et al., 2015; Lovallo et al., 1996, 2004; Mahmud and Feely, 2001; Miles-Chan et al., 2015; Mosqueda-Garcia et al., 1990; Noguchi et al., 2015; Notarius et al., 2006a, 2006b; Nussberger et al., 1990; Papaioannou et al., 2006; Papamichael et al., 2005; Passmore et al., 1987; Phan and Shah, 2014; Pincomb et al., 1996; Rachima-Maoz et al., 1998; Ragab et al., 2004; Ragsdale et al., 2010; Rakic et al., 1999; Rashti et al., 2009; Roberts et al., 2005; Robertson et al., 1978, 1981, 1984; Savoca et al., 2004, 2005; Shepard et al., 2000; Sondermeijer et al., 2002; Souza et al., 2014; Steinke et al., 2009; Strandhagen and Thelle, 2003; Stubbs and Macdonald, 1995; Sudano et al., 2005; Sung et al. 1994, 1995; Swampillai et al., 2006; Temple et al., 2010; Terai et al., 2012; Tse et al., 2009; Turley and Gerst, 2006; Turley et al., 2007, 2008; Ulanovsky et al., 2014; Umemura et al., 2006; van Dusseldorp et al., 1991; van Dusseldorp et al., 1989; Vlachopoulos et al., 2003b; Waring et al., 2003; Watson et al., 2000, 2002; Zimmermann-Viehoff et al., 2016; Agudelo-Ochoa et al., 2016; Brothers et al., 2016; Doerner et al., 2015; Domotor et al., 2015; Garcia et al., 2016; Hajsadeghi et al., 2016; Molnar and Somberg, 2015a; Papakonstantinou et al., 2016; Peveler et al., 2016; Shah et al., 2016; Teng et al., 2016). In 19 observational studies, individuals’ blood pressures were measured after ascertaining their average daily coffee and/or tea intake (Bakker et al., 2011; Bertrand et al., 1978; Chen et al., 2010; Giggey et al., 2011; Guessous et al., 2012; Hart and Smith, 1997; Larsson et al., 2008; Palatini et al., 1996; Reis et al., 2010; Stensvold et al., 1989; Vlachopoulos et al. 2005, 2007; Wakabayashi et al., 1998; Wang et al., 2011; Wilhelmsen et al., 1977; Wilson et al., 1989; Lopez-Garcia et al., 2016; Palatini et al., 2016; Rhee et al., 2016).

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Grant Support: NIH (R01EB002449-03).

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