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Carter, A. R.

Publications and source records attributed to Carter, A. R..

3 recordsLinked to original sources

Investigating the combined association of BMI and alcohol consumption on liver disease and biomarkers: a Mendelian randomization study of over 90 000 adults from the Copenhagen General Population Study

BackgroundBody mass index (BMI) and alcohol consumption are suggested to independently and interactively increase the risk of liver disease. We assessed this combined effect using factorial Mendelian randomization (MR).\n\nMethodsWe used multivariable adjusted regression and MR to estimate individual and joint associations of BMI and alcohol consumption and liver disease biomarkers (alanine aminotransferase (ALT) y-glutamyltransferase (GGT)) and incident liver disease. We undertook a factorial MR study splitting participants by median of measured BMI or BMI allele score then by median of reported alcohol consumption or ADH1B genotype (AA/AG and GG), giving four groups; low BMI/low alcohol (-BMI/-alc), low BMI/high alcohol (-BMI/+alc), high BMI/low alcohol (+BMI/-alc) and high BMI/high alcohol (+BMI/+alc).\n\nResultsIndividual positive associations of BMI and alcohol with ALT, GGT and incident liver disease were found. In the factorial MR analyses, considering the +BMI/+alc group as the reference, mean circulating ALT and GGT levels were lowest in the -BMI/-alc group (2.32% (95% CI: -4.29, -0.35) and -3.56% (95% CI: -5.88; -1.24) for ALT and GGT respectively). Individuals with -BMI/+alc and +BMI/-alc had lower mean circulating ALT and GGT compared to the reference group (+BMI/+alc). For incident liver disease multivariable factorial analyses followed a similar pattern to those seen for the biomarkers, but little evidence of differences between MR factorial categories for odds of liver disease.\n\nConclusionsConsistent results from multivariable regression and MR analysis, provides compelling evidence for the individual adverse effects of BMI and alcohol consumption on liver disease. Intervening on both BMI and alcohol may improve the profiles of circulating liver biomarkers. However, this may not reduce clinical liver disease risk.

epidemiology

A systematic review of sample size and power in leading neuroscience journals

Adequate sample size is key to reproducible research findings: low statistical power can increase the probability that a statistically significant result is a false positive. Journals are increasingly adopting methods to tackle issues of reproducibility, such as by introducing reporting checklists. We conducted a systematic review comparing articles submitted to Nature Neuroscience in the 3 months prior to checklists (n=36) that were subsequently published with articles submitted to Nature Neuroscience in the 3 months immediately after checklists (n=45), along with a comparison journal Neuroscience in this same 3-month period (n=123). We found that although the proportion of studies commenting on sample sizes increased after checklists (22% vs 53%), the proportion reporting formal power calculations decreased (14% vs 9%). Using sample size calculations for 80% power and a significance level of 5%, we found little evidence that sample sizes were adequate to achieve this level of statistical power, even for large effect sizes. Our analysis suggests that reporting checklists may not improve the use and reporting of formal power calculations.

scientific communication and education

rTMS with individualized resting-state network mapping for neuropsychiatric sequelae of repetitive traumatic brain injury in a retired NFL player

The recent advent of individualized resting-state network mapping (RSNM) has revealed substantial inter-individual variability in anatomical localization of brain networks identified using resting-state functional MRI (rsfMRI). Such variability may be particularly important after repetitive traumatic brain injury (TBI), which is associated with treatment-resistant depression. RSNM enables personalized targeting of repetitive transcranial magnetic stimulation (rTMS), a focal brain stimulation technique that relieves depression when administered over dorsolateral prefrontal cortex.\n\nRSNM was used to identify left/right dorsolateral prefrontal rTMS targets with maximal difference between dorsal attention network and default mode network (DMN) correlations. These targets were spatially distinct from those identified by prior methods. The method was evaluated by administering twenty sessions of left-sided excitatory and right-sided inhibitory rTMS to a retired NFL defensive lineman with progressive treatment-resistant neuropsychiatric disturbances. Treatment led to improvement in Montgomery-Asberg Depression Rating Scale (72%), cognitive testing, and headache scales. In comparison with healthy individuals and subjects with TBI-associated depression, baseline rsfMRI revealed substantially elevated DMN connectivity with medial temporal lobe (MTL). Serial rsfMRI scans showed gradual improvement in MTL-DMN connectivity and stimulation site connectivity with subgenual anterior cingulate cortex. This highlights the possibility of individualized neuromodulation and biomarker-based monitoring for neuropsychiatric sequelae of repetitive TBI.

neuroscience