Alcohol and brain structure across the lifespan: A systematic review of large-scale neuroimaging studies

Common functional polymorphisms in these genes are likely to be predictive (although each with small effect) alcohols effects on the brain: neuroimaging results in humans and animal models pmc of individualized pharmacological responses. As we have noted earlier, genetic studies, including case-control association studies and genome wide linkage studies, have identified associations between alcoholism and common functional polymorphisms in several candidate genes. Meanwhile, the current pharmacological therapies are only modestly effective in preventing relapse and dependence in alcoholics (Doggrell 2006; Kranzler and Van Kirk 2001; Mann 2004), prompting more research. Additionally, treating co-occurring disorders remains a challenge, and the use of creative approaches that would encompass individualized psychosocial support, as well as a combination of treatments, might be the most effective way to address this problem. To determine the influence of chronic ethanol intake on the central nervous system, we studied 40 asymptomatic, well-nourished, chronic alcoholics (mean age, 42.6 -+ 9.1 years) and 20 age-, sex-, and education-matched control subjects.

Alcohol Effects on Neural Correlates of Reward Processing and Cue-Reactivity

• In addition to the key MRS-visible metabolites NAA, tCr, and Cho, the combined resonance of glutamate (Glu) + glutamine (Gln), often referred to as Glx, has also been reported in the alcoholism literature.
• Hippocampal volume deficits in alcoholism are influenced by age (Sullivan et al. 1995), even though age-related decline is difficult to detect in cross-sectional studies (Pfefferbaum et al. 2013; Raz et al. 2010; Sullivan et al. 2005b).
• The limbic system monitors internal homeostasis, mediates memory and learning, and contributes to emotional feelings and behaviors.
• Relative to healthy controls, GABA levels were low and glutamate levels were high (but higher at T1 relative to T2) at both time points in the alcoholics (Brousse et al., 2012).
• Turning from studies with humans to animals, the following section examines imaging studies in models of alcoholism and related disorders.
• For example, in a recent cross-sectional, population-based study in which gender differences in cognitive performance were explored in relation to alcohol consumption (Yonker et al. 2005), drinking data were collected from men and women between 35 and 85 years of age, and the participants were classified into non, light, moderate, and heavy drinking subgroups.

Marchiafava-Bigami Disease (MBD) is marked by a mildly impaired mental status (e.g. confusion) and sometimes dysarthria (i.e., impairment of the speech)(H. Lee, Holburn, & Price, 2003) or ataxia (i.e., loss of control over bodily movement)(Arbelaez, Pajon, & Castillo, 2003). Although this disease is poorly understood, there exist indications that it may be linked to chronic alcohol consumption and nutritional deficiencies. MBD is traditionally characterized by demyelination and necrosis of the corpus callosum (Figure 1E) (Hillbom et al., 2014).

Neural Correlates of Family History of Alcohol Use Disorder and Level of Response

During the recovery phase, adolescent female mice treated with EtOH showed partial recovery from ethanol exposure. It is unclear, however, if the 2 weeks of recovery time afforded each mouse was sufficient to determine whether a full recovery is possible. Studies of the lasting consequences of repeated alcohol exposure during adolescence in animal models have identified numerous functional alterations across domains, ranging from cognition and behavior, to affect, and to later alcohol consumption.

Associated Data

Alcoholism’s effects on the brain and behavior are diverse, and are moderated or mediated by many factors (Oscar-Berman and Bowirrat 2005; Parsons 1996). In adults, males showed no interaction effect whilst adult females did; however, there were no significant differences of EtOH treatment within timepoints, suggesting that this interaction will need to be explored further before strong conclusions are drawn. Similar difficulties exist in interpreting the data for the somatosensory and cerebellar cortices in adult males and females. Research also has found compromised NAA/tCr levels in patients with cerebellar degeneration (Tedeschi et al. 1996; Terakawa et al. 1999). Two MRS case studies of MBD showed reduced NAA/tCr and elevated Cho/tCr in corpus callosum splenium (Gambini et al. 2003; Tuntiyatorn and Laothamatas 2008), findings consistent with demyelination (elevated Cho) and axonal injury (reduced NAA).

What do healthcare professionals who work with adolescents need to know about alcohol?

• To study the effects of alcohol exposure or withdrawal, alcohol is added to or removed from the fluid that supports and sustains the cells’ viability (i.e., the culture medium) (Hu and Ticku 1997).
• Normalization of NAA and Cho levels upon discontinuation of alcohol exposure seems to be translatable and indicates that some metabolic changes are directly linked to the toxicity of alcohol (Bartsch et al., 2007).
• Consequently, impulsivity seems to mediate alcohol abuse both as a dispositional risk factor and as a consequence of excessive drinking.
• In several regions (e.g., right frontal gyrus, bilateral temporal gyri, right insula), increased BOLD response was related to the low LR profile, whereas other regions (e.g., right precentral gyrus, left frontal gyrus, and left parietal lobule) showed the reverse with increased BOLD response relating to the high LR profile.
• In sum, although the extant literature primarily supports pre-existing differences in prefrontal- and limbic-related reward processing markers as a risk of subsequent alcohol use, emerging evidence suggests there may be a bidirectional relationship in other regions where alcohol use further modifies the neural processing and evaluation of rewards.
• However, it is unknown if sex differences in EtOH clearance are absent in adolescent mice; thus, it is unclear if age effects could be explained through this mechanism.

We then additionally adjusted for potential mediators including BMI, diabetes, hypertension, and number of comorbidities. When significant results were obtained in the ANOVA for alcohol group, we compared each drinking group to the light drinking group in post-hoc pairwise comparisons, with Bonferroni correction for multiple comparisons. A number of investigators have been using neuroimaging approaches to identify translational phenotypes related to alcohol dependence (Filbey et al., 2007; Heinz et al., 2007; Tapert et al., 2004; Wrase et al., 2007).

With the acceptance of neurogenesis, more studies have focused on its relation to the pathophysiology of neuro-psychiatric disorders includeing alcoholism. A strength of this study is the repeated assessment of alcohol use over time, which allowed us to differentiate never drinkers from former drinkers. Reported amounts of alcohol intake were relatively stable over the 22-year follow-up period, consistent with our prior report on the larger RBS cohort 39. In secondary analyses, we excluded the few participants from non-drinking, light-drinking and moderate-drinking groups who had a history of heavier drinking to determine whether this may have masked any protective associations of light or moderate drinking on brain-PAD, but results were unchanged. In closing, brain alterations underlying addiction not only drive the addiction process itself but also make it difficult for many people with AUD to change their drinking behavior, particularly if they are struggling to cope with the considerable discomfort of acute or protracted withdrawal. You can promote healthy changes in the brains and behaviors of patients with AUD by encouraging them to take a long-term, science-based approach to getting better.

Structural MRI

Further, there were no clear distinctions between age or sex on the alcohol effects on volumes of these two regions. Future higher‐powered studies will be required to delineate these effects and to uncover more subtle effects on individual ROIs. In contrast to cognitive functioning, aberrant emotional functioning in adolescent drinkers (especially with respect to facial emotion processing) appears to serve primarily as a risk factor for alcohol use in adolescence (e.g., Nikolova, et al., 2016). However, there are too few studies conducted in this area to rule out the possibility of alcohol-induced consequences. Prospective longitudinal fMRI studies involving tasks that tap into various aspects of emotion processing are greatly needed to confirm the stability of emotional networks in the context of adolescent alcohol use.

Participants.

Whereas chronic exposure to vaporized EtOH did not result in detectable effects on FA or MD, binge EtOH exposure resulted in transient decreases in FA and transient increases in MD (Pfefferbaum et al. 2015). Together, these results suggest that DTI can detect acute and subchronic effects on the brain, but that chronic exposure to EtOH can result in brain adaptations such that effects on FA and MD are no longer discernable. T1-weighted imaging in HE reveals bilateral, symmetrical, high-intensity signals in basal ganglia structures, particularly the globus pallidus and substantia nigra, probably due to manganese deposition and T1 shortening.

Researchers have studied this subjective quality of alcohol withdrawal by assessing threshold levels for the perception of rewarding stimuli. Such experiments found that alcohol initially lowers that reward threshold, because a weaker current is sufficient for the animal to perceive the stimulus as being rewarding. During alcohol withdrawal, however, the threshold for brain reward stimulation is significantly elevated (Schulteis et al. 1995). This model allows researchers to evaluate subtle aversive qualities of alcohol withdrawal that may contribute, at least in part, to the motivation for resuming drinking (i.e., relapse).

Rats that achieve binge-like BALs via gavage feeding show a larger effect (Zahr et al., 2010; Zahr, Mayer, Rohlfing, Hsu, et al., 2014; Zahr et al., 2013) than rats exposed to ethanol chronically via vapor (Pfefferbaum et al., 2008). The effect on ventricle size is transient in the binge models as ventricular volume recovers rapidly within one week of abstinence, contrary to the findings from human research (Sullivan & Pfefferbaum, 2009; Zahr & Pfefferbaum, 2017; Zahr, Rohlfing, et al., 2016). Similarly, studies in AUD patients shortly following detoxification have found low levels of Cho (Bendszus et al. 2001; Durazzo et al. 2004; Ende et al. 2005; Fein et al. 1994; Parks et al. 2002; Seitz et al. 1999), although Cho findings in AUD are less consistent (e.g., Hermann et al. 2012; Modi et al. 2011). Because these findings are prominent in white matter, it is thought that the effects of alcoholism are greater in white than in gray matter (De la Monte 1988; Harper et al. 2003). Relative to findings in WKS, research demonstrates mild volume deficits in the mammillary bodies (Shear et al. 1996; Sullivan et al. 1999), hippocampi, and thalami in uncomplicated alcoholics compared with healthy controls (De Bellis et al. 2005; Chanraud et al. 2007; Pitel et al. 2012; Sullivan 2003; van Holst et al. 2012).

In the past decade, there has been an increasing interest in alcoholism-related gender differences with respect to possible changes in brain and behavior (Lancaster 1995; NIAAA 1997; Nolen-Hoeksema and Hilt 2006; Wuethrich 2001). For example, in a recent cross-sectional, population-based study in which gender differences in cognitive performance were explored in relation to alcohol consumption (Yonker et al. 2005), drinking data were collected from men and women between 35 and 85 years of age, and the participants were classified into non, light, moderate, and heavy drinking subgroups. When these gender differences were examined by drinking group, visuospatial performance favoring men disappeared for the moderate to heavy drinking groups, but higher performance by women on episodic memory tasks was consistent across all levels of alcohol consumption. Results of neurobehavioral investigations tend to support the view that aging increases one’s vulnerability to alcoholism-related decline (Oscar-Berman and Marinkovic 2003). Significant correlations have been reported between age and regional MRI and DTI measures and performance on working memory, visuospatial ability, and gait and balance (Pfefferbaum et al. 2006), as well as in interhemispheric processing speed (Schulte et al. 2005).