Mystery of Cannabis-Induced Brain Changes Deepens

Over the last ten years, the use of cannabis explained the world over has risen dramatically due to its medical and recreational use becoming legalized in many countries. Such legalisation has taken place in the absence of full knowledge on what the impact of cannabis use is on the human brain.

Between the years 2006 and 2013 there was a reported increase of 250% of cannabis use in the last year in the United States among adults aged 65 years and older.1 Although the use of cannabis in older adults has increased, research pertaining to health outcomes in this demographic remains scarce. 

There are also findings to suggest negative effects of cannabis on cognitive abilities, as well as on brain structure and function. Which begs the question: is there a level of cannabis consumption that is risk free?

It remains unknown and adolescence as well as early adulthood entails cannabis abuse which is known to cause damage to the brain, however, even with the decades of ongoing cannabis use among older adults, its effects on the brains of people in this category are still few and far between.

Recently published in BMJ Mental Health journal, a study aimed to analyse both observational and genetic links of cannabis exposure on brain structure and functions. The UK Biobank is a longitudinal study which encompasses around 500000 subjects residing within UK.

These subjects were aged between 40-69 years at the time of their baseline evaluation which was done between 2006 to 2010. The inclusion criteria and other characteristics of subject members of the UK Biobank were included in the study.

The anthropometric data employed in this research were collected during the first repeat assessment visit (2012–2013), and the first imaging visit (2014–2019). Cannabis self-report data (described below) collected at the assessment visit was accessible for 157316 participants. MRI and demographic data used in this research was obtained during the imaging visit.  

UK Biobank team developed exclusion criteria with respect to MRI scanning that includes quite conventional MRI safety/quality criteria like exclusion because of the presence of metallic implants, recent surgery or any medical condition that contraindicates MRI such as hearing impairment, difficulty in breathing, or severe claustrophobia.

Also, in the course of the study, raw MRI data which had incorrect dimensions, was damaged, unavailable, or otherwise did not meet the standards for further processing was discarded.

In the present investigation of the 157316 records on cannabis use available for analysis, 141420 were eliminated for the reason of no MRI data collection or in some other situation missing confounding variables only. There were no other exclusion criteria. Therefore, the final analysis included 15896 subjects with complete cases. 

Various measures of brain structure and function were associated with cannabis use. In comparison to non-users, users’ white matter integrity, particularly in the genu of the corpus callosum, was assessed via global measures of fractional anisotropy and mean diffusivity and found to be significantly poorer.

Additionally, resting-state functional connectivity of the brain was also weaker in regions involved in the default mode and central executive networks in the users. However, Mendelian randomisation analyses showed no evidence of causation in the associations of cannabis use with brain structure or its directly related functions. 

It is unlikely that associations between lifetime cannabis use and brain structure and function in later life are causal, and they may simply be residual confounding.  

However, we have a few limitations in our study. First, as for the sample size, it was significantly larger in comparison with nearly every other study, though it is important to bear in mind that in the farther prospective investigations, more attention will be paid to the general healthy population.

Selection bias was also identified on the sociodemographic, physical, lifestyle and health related characteristics than on a population sample illustrated by lower prevalence of cannabis use disorder.  

Besides, blank focuses on an absolutely different problem – one that relates to decision about drugs and is not appropriate for consideration of cannabis use disorders given the low number of participants with this diagnosis.  

Habitual cannabis uses across the life span predicted cognitive ability and several aspects of brain structure in later life, particularly in the corpus callosum. This was not Jack the genetic analysis did not support the ideas that these associations were reason down to cause and effect.  

That is, these findings could stem from residual confounding, meaning there exist other variables that confound the relative risk in the observational analysis but was not accounted for. Hence, inconclusively one has to muster up a lot of care in coming to any conclusions from our findings.  

Further attempts should be made to determine the consequences of the high use of cannabis in such given populations particularly on potency and other information that should inform policy.