Difference in distribution functions: A new diffusion weighted imaging metric for estimating white matter integrity

Du, Jing; Koch, Forrest; Xia, Aihua; Jiang, Jiyang; Crawford, John D.; Lam, Ben C. P.; Thalamuthu, Anbupalam; Lee, Teresa; Kochan, Nicole A.; Fawns-Ritchie, Chloë; Brodaty, Henry; Xu, Qun; Sachdev, Perminder S.; Wang, Wen

doi:10.1016/j.neuroimage.2021.118381

Cited by 8 publications

(13 citation statements)

References 39 publications

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“… 42 , 44 In the current study, past‐year binge‐drinking at baseline was associated with DDF at Wave 2, a newly developed automated neuroimaging marker of white matter integrity using dMRI data. 22 This relationship was robust to the inclusion of demographic and clinical confounders, as well as when former drinkers and those with incident dementia were excluded. Using both Sydney MAS and UK Biobank data, this measure has been shown to be more strongly correlated with both age and cognition when compared with other dMRI metrics, such as fractional anisotropy (FA), mean diffusivity (MD) and peak width of skeletonised mean diffusivity (PSMD).…”

Section: Discussionmentioning

confidence: 87%

“…This relationship was robust to the inclusion of demographic and clinical confounders, as well as when former drinkers and those with incident dementia were excluded. Using both Sydney MAS and UK Biobank data, this measure has been shown to be more strongly correlated with both age and cognition when compared with other dMRI metrics, such as fractional anisotropy (FA), mean diffusivity (MD) and peak width of skeletonised mean diffusivity (PSMD) 22 . In the current study, DDF captured a subtle negative relationship between past‐year binge drinking and white matter microstructure (indicative of poorer white matter integrity), which was not apparent using other measures of white matter integrity, including PSMD and WMH burden.…”

Section: Discussionmentioning

confidence: 99%

“…Based on previous studies 8 , 9 , 10 , 15 , 21 examining the alcohol–brain relationship, we focused on total grey matter volume and total white matter volume, as well as specific regions of interest (ROIs), namely, the hippocampus, thalamus, amygdala, corpus callosum, orbitofrontal cortex and insula. Outcomes related to white matter integrity were volume of deep and periventricular WMH, as well as whole brain difference in distribution functions (DDF as acquired via dMRI 22 ) and peak skeletonised mean diffusivity (PSMD as acquired by dMRI 23 ). As with previous studies using MAS data, WMH volume was log transformed to obtain a normal distribution.…”

Section: Methodsmentioning

confidence: 99%

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Longitudinal alcohol‐related brain changes in older adults: The Sydney Memory and Ageing Study

Mewton,

Visontay,

Hughes

et al. 2024

Addiction Biology

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Increases in harmful drinking among older adults indicate the need for a more thorough understanding of the relationship between later‐life alcohol use and brain health. The current study investigated the relationships between alcohol use and progressive grey and white matter changes in older adults using longitudinal data. A total of 530 participants (aged 70 to 90 years; 46.0% male) were included. Brain outcomes assessed over 6 years included total grey and white matter volume, as well as volume of the hippocampus, thalamus, amygdala, corpus callosum, orbitofrontal cortex and insula. White matter integrity was also investigated. Average alcohol use across the study period was the main exposure of interest. Past‐year binge drinking and reduction in drinking from pre‐baseline were additional exposures of interest. Within the context of low‐level average drinking (averaging 11.7 g per day), higher average amount of alcohol consumed was associated with less atrophy in the left (B = 7.50, pFDR = 0.010) and right (B = 5.98, pFDR = 0.004) thalamus. Past‐year binge‐drinking was associated with poorer white matter integrity (B = −0.013, pFDR = 0.024). Consuming alcohol more heavily in the past was associated with greater atrophy in anterior (B = −12.73, pFDR = 0.048) and posterior (B = −17.88, pFDR = 0.004) callosal volumes over time. Across alcohol exposures and neuroimaging markers, no other relationships were statistically significant. Within the context of low‐level drinking, very few relationships between alcohol use and brain macrostructure were identified. Meanwhile, heavier drinking was negatively associated with white matter integrity.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Longitudinal alcohol‐related brain changes in older adults: The Sydney Memory and Ageing Study

Mewton,

Visontay,

Hughes

et al. 2024

Addiction Biology

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“…Seven Global cognition was computed by averaging the scores across all three cognitive domains and again standardising against the healthy subsample. Further details of the standardisation procedure can be found in our previous work using the UK Biobank data 28 .…”

Section: Cognitive Testsmentioning

confidence: 99%

White matter brain age as a biomarker of cerebrovascular burden in the ageing brain

Pan

Jiang

et al. 2022

Preprint

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As the brain ages, it almost invariably accumulates vascular pathology, which differentially affects the white matter. The microstructure of the white matter may therefore reveal a brain age reflecting cerebrovascular disease burden and a relationship to vascular risk factors. In this study, a white matter specific brain age was developed from diffusion weighted imaging (DWI) using a three-dimensional convolutional neural network (3D-CNN) deep learning model in both cross-sectional data from UK biobank participants (n = 37327) and a longitudinal subset (n = 1409) with an average of 2.25 years follow up. We achieved a mean absolute error (MAE) of white matter brain age prediction of 2.84 years and a Pearson’s r of 0.902 with chronological age in the test participants. The average white matter brain age gap (WMBAG) of the baseline 1409 participants with repeated scans were 0.36 ± 0.11 years younger than that of other participants in the baseline test sample with single time-point MRI scan (n = 9759). Individual vascular risk factors and the cumulative vascular risk score were significantly correlated with greater WMBAG Obesity was observed to be correlated with WMBAG only in the male participants. Participants with one, two, and three or more vascular risk factors, compared to those without any, showed an elevated WMBAG of 0.54, 1.23, and 1.94 years, respectively. Baseline WMBAG was also associated significantly with processing speed, executive and global cognition after Bonferroni correction. The significant associations of diabetes and hypertension with poor processing speed and executive function were found to be mediated through the WMBAG. However, the vascular risk factors did not associate with the two-year change in WMBAG in the longitudinal dataset. Our analysis suggests that tissue-specific brain age can be successfully targeted for the examination of the most relevant risk factors and cognition, although longer-term longitudinal data are needed to demonstrate its dynamic characteristics. The results suggest an intriguing possibility that a white matter brain age gap can serve as a potential neuroimaging biomarker for an individual’s cerebrovascular ageing process.

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“…• экспрессии рецепторов нейротрофических и ростовых факторов, регуляторов роста; • выживания клеточных систем [65]. J.R. Conde, W.J.…”

Section: взаимосвязь изменений когнитивных процессов и кишечной микро...unclassified

Mechanisms of Influence of Intestinal Microbiota on the Processes of Aging of the CNS and the Formation of Cognitive Disorders in Alzheimer’s Disease

et al. 2022

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Background: the increase in the life expectancy of a modern person is accompanied by an increase in the prevalence of neurocognitive disorders. Various indicators associated with biological age are consistent with neurocognitive deficits. In the process of ontogeny, a complex symbiotic relationship develops between the host and the microbe. Presumably, they are realized along the microbiota-gut-brain axis. The participation of the intestinal microbiota in the ontogeny of the brain is assumed. The purpose of review: based on a systematic review of the scientific literature, to summarize research data on the mechanisms of the influence of the intestinal microbiota on the aging processes of the central nervous system and the formation of cognitive disorders in Alzheimer’s disease.Materials and methods: 27 Russian-language and 257 English-language articles were selected from MedLine/PubMed and eLibrary from 2000 to 2022 by the keywords “gut microbiota”, “neurocognitive disorders”, “aging”, “neurodegeneration”, “Alzheimer’s disease”. The hypothesis about the participation of the microbiota in cerebral ontogeny made it possible to select 110 articles for analysis.Conclusion: this scientific review reflects the authors’ ideas about the systemic mechanisms of normal and pathological aging of the CNS and the multifactorial nature of the pathogenesis of neurocognitive disorders.

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Difference in distribution functions: A new diffusion weighted imaging metric for estimating white matter integrity

Cited by 8 publications

References 39 publications

Longitudinal alcohol‐related brain changes in older adults: The Sydney Memory and Ageing Study

Longitudinal alcohol‐related brain changes in older adults: The Sydney Memory and Ageing Study

White matter brain age as a biomarker of cerebrovascular burden in the ageing brain

Mechanisms of Influence of Intestinal Microbiota on the Processes of Aging of the CNS and the Formation of Cognitive Disorders in Alzheimer’s Disease

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