Abstract:Alcohol and cannabis use disorder (AUD/CUD) are two of the most common addictive disorders. While studies are beginning to understand the neural changes related to acute and chronic use, few studies have examined the independent effects of AUD and CUD on neural oscillatory activity. We examined 45 adults who reported current use of both cannabis and alcohol. Participants underwent the SCID-V to determine whether they met criteria for AUD and/or CUD. Participants also completed a visual-spatial processing task … Show more
“…4 and Supplementary Table S7 ). This result shows that the ELOVL7 SE may impact specific brain regions, including the visual cortex which plays a role in alcohol addiction [ 64 , 65 ]. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, the occipital cortex is activated by drug cues including alcohol, as functional MRI signaled significant alcohol or drug-elicited activity in the left BA 19 and BA 17 [ 65 ]. In a recent study, AUD was found to be associated with change of the alpha oscillatory activity in the occipital cortex, indicating that the visual cortex plays a role in alcohol addiction [ 64 ]. In addition, the auditory cortex, i.e., Heschl’s gyrus, was impacted by the ELOVL7 splicing event on both hemispheres.…”
Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.
“…4 and Supplementary Table S7 ). This result shows that the ELOVL7 SE may impact specific brain regions, including the visual cortex which plays a role in alcohol addiction [ 64 , 65 ]. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, the occipital cortex is activated by drug cues including alcohol, as functional MRI signaled significant alcohol or drug-elicited activity in the left BA 19 and BA 17 [ 65 ]. In a recent study, AUD was found to be associated with change of the alpha oscillatory activity in the occipital cortex, indicating that the visual cortex plays a role in alcohol addiction [ 64 ]. In addition, the auditory cortex, i.e., Heschl’s gyrus, was impacted by the ELOVL7 splicing event on both hemispheres.…”
Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.
“…Importantly for studies of hypertension, the measured signals are immune to neurovascular coupling changes and provide a direct measure of neural activity. These oscillations underlie a wide range of cognitive functions and have previously been used in a wide range of clinical populations, including HIV, substance use, diabetes and Alzheimer's (Arif et al, 2020;Embury et al, 2018;Lew et al, 2018;Lew et al, 2021;Schantell et al, 2022;Springer et al, 2022). Specifically, alpha and gamma oscillatory activity and connectivity are critical elements underlying successful selective attention processes, with the previous literature showing sensitivity of these neural responses to developmental, ageing and pathophysiological changes (Arif et al, 2023;Lew et al, 2018;McDermott et al, 2017;Proskovec et al, 2018;Son et al, 2023;Taylor et al, 2021;.…”
Hypertension‐related changes in brain function place individuals at higher risk for cognitive impairment and Alzheimer's disease. The existing functional neuroimaging literature has identified important neural and behavioural differences between normotensive and hypertensive individuals. However, previously‐used methods (i.e. magnetic resonance imaging, functional near‐infrared spectroscopy) rely on neurovascular coupling, which is a useful but indirect measure of neuronal activity. Furthermore, most studies fail to distinguish between controlled and uncontrolled hypertensive individuals, who exhibit significant behavioural and clinical differences. To partially remedy this gap in the literature, we used magnetoencephalography (MEG) to directly examine neuronal activity that is invariant to neurovascular coupling changes induced by hypertension. Our study included 52 participants (19 healthy controls, 15 controlled hypertensives, 18 uncontrolled hypertensives) who completed a modified flanker attention task during MEG. We identified significant oscillatory neural responses in two frequencies (alpha: 8–14 Hz, gamma: 48–60 Hz) for imaging and used grand‐averaged images to determine seeds for whole‐brain connectivity analysis. We then conducted Fisher‐z tests for each pair of groups, using the relationship between the neural connectivity and behavioural attention effects. This highlighted a distributed network of regions associated with cognitive control and selective attention, including frontal‐occipital and interhemispheric occipital connections. Importantly, the inferior frontal cortex exhibited a unique neurobehavioural relationship that distinguished the uncontrolled hypertensive group from the controlled hypertensive and normotensive groups. This is the first investigation of hypertension using MEG and identifies critical whole‐brain connectivity differences based on hypertension profiles.
imageKey points
Structural and functional changes in brain circuitry scale with hypertension severity and increase the risk of cognitive impairment and Alzheimer's disease.
We harness the excellent spatiotemporal precision of magnetoencephalography (MEG) to directly quantify dynamic functional connectivity in healthy control, controlled hypertensive and uncontrolled hypertensive groups during a flanker task.
In the first MEG study of hypertension, we show that there are neurobehavioural relationships that distinguish the uncontrolled hypertensive group from healthy and controlled hypertensive group in the prefrontal cortex.
These results provide novel insights into the differential impact of hypertension on brain dynamics underlying selective attention.
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