However, this finding was only significant in women and was weaker and no longer significant after bronchodilator use. In the same birth cohort at age 45, Hancox et al further reported a significant negative association of marijuana joint years with forced expiratory flow at 25% and 75% of the pulmonary volume, but this association was only significant in men.A dose-response effect could also be consistent with previous findings by Pletcher et al who followed a cohort of 5015 young adults with a high tobacco-smoking prevalence for over 20 years and found no evidence that increasing lifetime marijuana exposure adversely affected lung function except among those with very heavy lifetime exposure . The findings of the present study should be interpreted in the context of certain limitations. SPIROMICS was not specifically designed to examine the effects of marijuana smoking, and our analyses were conducted post hoc; therefore, this analysis may be under powered due to a relatively small sample size and short duration of followup and our findings should be considered exploratory. SPIROMICS did not enroll a random sample, so that our results may not be generalizable. Marijuana is inhaled by various methods besides smoking a joint,4×4 grow table including the use of a pipe or bong, hookah, a blunt, dabbing, vaping, or administered as edible cannabinoids,all of which information was not collected at the baseline visit.
However, the most common mode of inhalation of marijuana is via smoking a joint,but the amount of marijuana actually delivered with each use is highly variable and difficult to quantitate so the method we used for quantitating the cumulative lifetime amount of marijuana smoked is crude. Besides, marijuana use was self-reported and thus, prone to recall or reporting biases since marijuana use at some sites was illicit at the time of data collection. Our classification of the participants with respect to marijuana- and tobacco-use status and the lifetime amount of use was based on the information collected at baseline that did not take into account changes in marijuana or tobacco amount or use status during the follow-up period. Moreover, the groups we compared both by marijuana-smoking status and by joint years were quite different, and we could not adequately control for all of the differences. Therefore, between-group differences in the true amount and modes of exposure to marijuana, as well as in socioeconomic differences, might explain any effects noted. Finally, since most participants with a history of marijuana smoking were relatively light users , it is possible that the cumulative amount of self-reported marijuana exposure was insufficient to have a detectably deleterious effect on lung health on top of the impact of a history of comparatively heavy tobacco smoking. The present study also has several strengths. Participants were recruited and followed at 12 geographically varied sites nationwide, and women and African Americans were adequately represented, suggesting at least some measure of generalizability. All participants had extensive baseline and longitudinal characterization, allowing assessment of multiple clinical outcomes over several years.
Spirometry and HRCT imaging were performed by strict adherence to recommended standards and protocols and were interpreted by dedicated reading centers. A relatively large number of participants were current marijuana smokers or reported a heavy lifetime exposure to marijuana, thereby, allowing for an assessment of dose-response relationship.ADOLESCENCE IS AN IMPORTANT developmental period associated with significant increases in alcohol and marijuana use . Sixty-eight percent of American 12th graders endorse lifetime alcohol use, with more than 20% reporting recent heavy episodic drinking . Marijuana is commonly used in conjunction with alcohol , as 45% endorse lifetime use of marijuana by 12th grade . High rates of adolescent alcohol and marijuana use are concerning, given the significant neurodevelopment in gray and white matter during this period. Gray matter, consisting of neurons and glialcells, increases in volume during childhood and decreases during early adolescence. Gray matter reduction may represent the pruning of excess synapses, white matter encroachment, and/or changes in the extracellular matrix . White matter continues to increase linearly throughout adolescence, likely driven by progressive axonal myelination . Both processes are associated with more efficient cognitive development, and any neurotoxic insults during these crucial processes could have long-lasting implications for cognitive development . Cross-sectional neuropsychological findings show that heavy marijuana and alcohol users perform worse on tests of psychomotor speed, complex attention, story memory, and planning and sequencing abilities, even after a month of abstinence , and show deficits on tests of verbal and visual memory . Longitudinal examinations have found that subtle deficits in cognitive functioning may remit with abstinence to some degree; however, this may not be the case for all aspects of cognitive functioning .
Early initiation of marijuana use in particular may have long-lasting consequences in sustained attention, executive functioning , impulse control, and verbal memory . Underlying brain structural changes, particularly cortical thinning, may help explain the cognitive abnormalities found in alcohol- and marijuana-using teens. Cross-sectional structural magnetic resonance imaging studies have found thinner cortices in prefrontal and insular regions and thicker cortices in posterior regions in marijuana-using adolescents when compared to controls . It remains unclear if structural differences exist before marijuana use. Although structural neuroimaging studies show marijuana-related effects on tissue , smaller orbitofrontal volumes at age 12 predict marijuana initiation by age 16, suggesting cross-sectional findings may be partially attributable to premorbid structural brain differences . Perhaps an interaction of vulnerability and exposure leads to continued use and poorer neural and cognitive outcomes. Several functional neuroimaging studies have shown aberrations in brain response patterns and cerebral blood fl ow in marijuana- and alcohol-using adolescents, which may partially be explained by aberrant cortical thinning . Abstinence may aid in tissue recovery to some extent and diminish the observed marijuana-related differences in neural functioning . However, studies suggest deficits persist even after a month . The aims of this study were to examine the impact of heavy marijuana and alcohol use on cortical thickness in adolescents before and after 28 days of monitored abstinence. We hypothesized that heavy marijuana and alcohol users, compared to controls, would demonstrate thicker cortices across independent standardized neuroanatomical cortical regions at both baseline and follow-up because of altered neurodevelopmental trajectories . We did not expect considerable within-group brain change in cortical thickness after 4 weeks of monitored abstinence in either group. Nevertheless, this has not been previously explored in the literature to our knowledge, and we predicted that, along with a between-group effect, substance users might demonstrate greater improvement in cortical thickness , along with neurocognitive performance, during 1 month of abstinence from marijuana use.Adolescents were recruited from local San Diego schools and included 24 heavy marijuana users who regularly used alcohol and 30 control teens with minimal substance use histories . Teens were recruited for cannabis drying system use; however, the majority of users also reported heavy lifetime alcohol use . Comprehensive screening interviews were administered to adolescents and parents/guardians; adolescents provided assent for their own participation, and guardians were required to provide consent in accordance with the University of California, San Diego Human Research Protections Program. Exclusionary criteria were history of a Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition, Text Revision , Axis I disorder other than alcohol or cannabis use disorder; psychoactive medications; learning disability or mental retardation; neurological condition or traumatic brain injury with loss of consciousness greater than 2 minutes; prenatal alcohol or other drug exposure; premature birth; left handedness; and non-fluency in English.
Participants received neuroimaging and neuropsychological, substance use, and mental health assessment at baseline and follow-up . Participants were asked to refrain from using all intoxicants for 28 days and underwent biweekly urine toxicology screening to examine 11-nor- 9-carboxy-tetrahydrocannabinol /creatinine excretion ratios for confirmation of completing the marijuana abstinence protocol . New cannabis use was determined by dividing each THCCOOH normalized to creatinine concentration collected by the previously collected specimen and factoring in time intervals between collections, per Huestis and Cone recommendations for determining new cannabis use as a function of time . A change in metabolite/creatinine ratios greater than 1.5 is considered new use. Eight of our 24 users reported f4 days of light use within the fi rst week of the abstinence period; however, we included them as abstinent given their decreasing THCCOOH/creatinine ratios . Breath alcohol analysis was given at each in-person appointment to help affi rm abstinence from alcohol; we did not have any positive breath-alcohol-analysis tests. For those individuals successfully completing the protocol and demonstrating decreasing THCCOOH ratios, self-reported alcohol use over the 28 days was f5.The neuroimaging software FreeSurfer, which is well documented and freely available , was used for cortical surface reconstruction and thickness estimates . The initial cross-sectional processing involves motion correction and averaging of T1 weighted images, removal of non-brain tissue and transformation to standardized space, segmentation of sub-cortical white and deep gray matter structures, intensity normalization, and tessellation of the gray/white matter boundary. Local MRI intensity gradients then guide a surface deformation algorithm to place smooth borders where the greatest shift in intensity defines transition to other tissue classes ; this procedure allows for quantification of sub-millimeter group differences . Cortical thickness was calculated as the closest distance from the gray/white matter boundary to the gray matter/ cerebral spinal fluid boundary at each vertex on the cortical surface . Validity of the cortical thickness measurement procedures has been verified using manual measurements and histological analysis . Test–retest reliability across scanners and field strengths has been shown using these standardized procedures . Following cross-sectional processing of all time points, data were next fed through the longitudinal processing stream in FreeSurfer . This approach extracts reliable volume and thickness estimates by creating an unbiased within-subject template space and image from the two cross-sectionally processed time points using a consistent robust inverse registration method . Processing steps such as Talairach transforms, atlas registration, and spherical surface maps and parcellations are initialized with common information from the within-subject template, increasing reliability and statistical power . One rater , blind to participant characteristics, followed the reconstruction and longitudinal edit procedures to identify and correct any errors made during the cortical reconstruction process. This involved verification of the automated skull stripping and a coronal plane slice-by-slice inspection of the gray/white and gray/cerebral spinal fluid surfaces. No editing was necessary following the longitudinal processing, although all longitudinal runs were checked for quality. Following inspection, an automated parcellation procedure divided each hemisphere into 34 independent cortical regions based ongyral and sulcal features . Cortical thickness estimates averaged over each parcellation region were extracted for statistical analyses in SPSS.Analysis of variance and chi-square tests were run between groups to evaluate differences on demographic variables and to identify appropriate covariates for subsequent analysis. Cortical thickness measurement. Repeated-measures analysis of covariance examined main effects of time, group, and Group × Time interactions on cortical thickness values for 34 independent standard neuroanatomical cortical regions in each hemisphere. Intracranial volume was included as a covariate. Marijuana and alcohol are commonly used concomitantly . In fact, more than 80% of marijuana users in our studies report regular alcohol use. Given the literature on the deleterious effects of alcohol on neurodevelopment and between group differences known to exist in this sample, lifetime alcohol use was specified a priori and statistically adjusted for in follow-up post hoc ANCOVAs examining group differences at each time point for regions in which a main effect of group or interaction was identified. Secondary analyses further evaluating the impact of substance use on cortical thickness included exploratory bivariate correlations between substance use variables and cortical thickness estimates at each time point in the user group . Neuropsychological performance. Repeated-measures ANCOVA was used to evaluate neurocognitive performance over time with alcohol as a covariate for each neurocognitive subtest. Bivariate correlations between neurocognitive performance and cortical thickness estimates were explored; if significant associations were identified, relationships between cortical thickness in that region and individual domain scores were examined within each group to identify correlates driving the relationship. Associations between age of onset of alcohol and marijuana use and neuropsychological outcome data were also explored in the user group.We prospectively examined cortical thickness estimates and neurocognition in a sample of adolescent heavy marijuana and alcohol users and matched controls before and after 28 days of monitored abstinence.