We found cortical gray matter volume reductions (primarily in prefrontal and parietal regions) in male heavy drinkers who met criteria for alcohol dependence, but had never been in treatment. The cortical volume loss was not correlated with family history of alcoholism or with education, suggesting that the volume loss reflects the effect of alcohol ingestion, rather than premorbid factors that predispose subjects to heavy drinking. Unlike most other studies of structural brain changes (which used samples drawn from treatment), this treatment-naive sample showed no white matter {
Pfefferbaum, 1995 #2911;
Shear, 1994 #1722;
Harper, 1988 #1723;
de la Monte, 1988 #3178;
Jernigan, 1992 #3180} or temporal lobe {
Jernigan, 1991 #2898;
Pfefferbaum, 1992 #827;Pfefferbaum, 1997 #2989;
Sullivan, 1995 #772} volume loss. Our findings are consistent with the hypothesis that structural brain changes in treatment-naive alcoholics are less severe than those reported in clinical samples of alcoholics. However, caution must be taken when comparing our findings with results from clinical samples, as we did not directly compare treatment-naive alcoholics with treated alcoholics. In addition, our treatment-naive sample tended to be younger than the (clinical) samples reported in the literature. Given that increasing age magnifies the effects of alcohol on brain structure and function {
Carlen, 1978 #1068;
Wilkinson, 1985 #918;
Jernigan, 1986 #884;
Lishman, 1987 #1083;
Ron, 1983 #1087}, the younger age of our sample compared to clinical samples in the literature may contribute to the less morbid structural imaging findings in our study.
Preferential prefrontal gray matter atrophy associated with alcohol abuse was first suggested by Courville {
Courville, 1955 #871} in 1955. Prefrontal atrophy has since become one of the most frequent findings in investigations of the CNS effects of alcohol dependence {
Harper, 1990 #812;Pfefferbaum, 1997 #2989;Gilman, 1990 #1794;Adams, 1993 #1803;
Pfefferbaum, 1995 #2911}. Preferential frontal lobe involvement in alcoholism has also been documented with PET {
Wang, 1993 #1715;
Volkow, 1992 #1716;
Risberb, 1987 #3172}, and in studies of cortical neuronal counts {
Kril, 1994 #3173;
Harper, 1989 #811;
Harper, 1987 #810;
Harper, 1990 #812;
Kril, 1989 #887}.
While our strongest findings were in the prefrontal cortex, parietal cortex was also adversely affected by heavy drinking. Jernigan also found parietal cortex atrophied in a MRI study of abstinent alcoholics {
Jernigan, 1991 #2898}. Parietal gray matter volume reductions are consistent with the frequent findings of alcohol-related impairments in visuo-spatial abilities and sensory integration {
Sullivan, 2000 #3191}.
We did not observe lateralized reductions in cortical volume. This does not support the right hemisphere model of the effects of alcoholism on brain function {
Hutner, 1996 #3181}. Purported right hemisphere tasks are often novel tasks requiring new learning, which is dependent on prefrontal cortex. They also involve spatial (rather than verbal) processing of stimuli, which is dependent on parietal cortex. We hypothesize that ‘right hemisphere impairment’ is actually impairment in functions subserved by prefrontal and parietal cortices.
There was no evidence of white matter loss in the HD sample. This is in contrast to studies of alcohol dependent samples drawn from treatment settings where white matter loss is a common finding. (However, as noted above, this study is not a direct comparison of treatment-naïve and clinical samples of alcoholics.) Our finding of intact white matter volume on structural MRI in these treatment-naive subjects occurred in the context of a 13% reduction in the
31P MRS broad component measured in the white matter of a subset of the HD subjects compared to LD {
Estilaei, 2001 #3168}. This suggests higher rigidity of white matter phospholipids in the absence of white matter volume loss. Our hypothesis is that alterations in the composition of membrane lipids lead to changes in myelin structure, and, eventually, to tissue volume loss. If this is true, then
31P MRS broad component measures should be even more reduced in clinical samples, where they occur in the presence of white matter volume reductions. We also found
1H MRS evidence for pre-atrophic white matter n-acetylaspartate (NAA) reductions in a subset of the HD sample compared to LD {
Goldmann, 2000 #3170}. Similar to the argument regarding
31P MRS measures, we hypothesize that the white matter NAA reductions will be larger in clinical samples where they are likely to occur in the context of white matter volume loss.
In the HD sample (and the age-comparable HD subgroup) we found strong correlations of reductions in total and regional cortical gray matter volume with age and with lifetime duration of alcohol use; however, age and duration of alcohol use were almost totally confounded. LD showed a strong trend toward association of age with total cortical gray matter, but not with any regional gray matter measures. This suggests that long-term alcohol dependence as the most likely cause of the prefrontal gray matter volume reductions in the HD sample. However, we cannot definitively say whether the volume reductions in HD are associated with long-term heavy alcohol use together with increasing age, or simply with duration of alcohol use. Given that the older drinkers have a longer duration of alcohol use, the simplest interpretation of the data would be that duration of alcohol use is the operative factor in cortical volume loss in alcohol dependent individuals. This interpretation is not consistent with the literature, which tells us that there is a greater degree and persistence of irreversible brain atrophy in older compared to younger alcoholics, independent of the duration of their drinking {Fein, 1990 #767}.
There may be other manifestations of the bias that occurs when findings of studies of treated alcoholics are presumed to apply to all alcoholics. It is possible that there is greater psychiatric comorbidity in clinical samples than in treatment-naive samples of alcoholics. We know that comorbidity of substance use and psychiatric disorders is substantial. The Epidemiology Catchment Area (ECA) Study {
Narrow, 1993 #3188} found a history of psychiatric disorder in 35% of the 13.5% of the general population who had a history of alcohol abuse. The ECA estimates on comorbidity of psychiatric and alcohol abuse disorders has been replicated by the more recent National Comorbidity Survey data {
Kessler, 1994 #3186}. Among individuals in alcohol and drug abuse treatment, estimates are that up to 80% have psychiatric symptoms {
Kosten, 1988 #3187}. These epidemiological data address coexisting psychopathology that is severe enough to meet criteria for a psychiatric disorder. This is an underestimate of coexisting psychopathology in that it does not address pathology that is of insufficient severity to result in a clinical diagnosis (e.g., depression or bipolar affective symptoms, antisocial personality traits, attention deficit hyperactivity disorder traits, posttraumatic stress disorder symptoms, and other substance abuse history). Although we did not directly assess psychiatric comorbidity in the study sample, we hypothesize that treatment-naïve samples have less psychiatric comorbidity than clinical samples of alcoholics.
We only examined men in this study. The bias inherent in studying clinical populations may be different for men and women, and the greater CNS consequences reported for female versus male clinical samples {
Jacobson, 1986 #1079;
Bergman, 1987 #764} may reflect this difference. The more morbid CNS findings for women may be spurious if clinical samples of alcoholic women differ from treatment-naive alcoholic women more than do clinical versus treatment-naive samples of alcoholic men. This is entirely possible, since women (for a variety of reasons) are less likely than men to receive treatment for alcohol problems [Conference on Substance Abuse and the American Woman at the Center on Addiction and Substance Abuse at Columbia University, 1996]. Therefore, clinical samples versus treatment-naive samples of female alcoholics may differ in severity of alcoholism or prevalence and severity of concomitant psychopathology than do clinical versus treatment-naive samples of male alcoholics.
Alcoholics in treatment need to be compared directly to non-treatment seeking alcohol dependent individuals to determine whether clinical samples differ from treatment-naive samples on measures of CNS structure and function. Coexisting psychopathology, prevalence and severity of predisposing factors (which may be associated with premorbid abnormalities in CNS structure and function), and severity of alcoholism should be assessed. Finally, we need to examine the “more vulnerable” female alcoholic pictured in the literature; are these findings a function of a bias toward sicker individuals in female versus male clinical populations?
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