Dataset Information

Sex differences in gray matter volume: how many and how large are they really?

ABSTRACT: BACKGROUND:Studies assessing volumetric sex differences have provided contradictory results. Total intracranial volume (TIV) is a major confounding factor when estimating local volumes of interest (VOIs). We investigated how the number, size, and direction of sex differences in gray matter volume (GMv) vary depending on how TIV variation is statistically handled. METHODS:Sex differences in the GMv of 116 VOIs were assessed in 356 participants (171 females) without correcting for TIV variation or after adjusting the data with 5 different methods (VBM8 non-linear-only modulation, proportions, power-corrected-proportions, covariation, and the residuals method). The outcomes obtained with these procedures were compared to each other and to those obtained in three criterial subsamples, one comparing female-male pairs matched on their TIV and two others comparing groups of either females or males with large/small TIVs. Linear regression was used to quantify TIV effects on raw GMv and the efficacy of each method in controlling for them. RESULTS:Males had larger raw GMv than females in all brain areas, but these differences were driven by direct TIV-VOIs relationships and more closely resembled the differences observed between individuals with large/small TIVs of sex-specific subsamples than the sex differences observed in the TIV-matched subsample. All TIV-adjustment methods reduced the number of sex differences but their results were very different. The VBM8- and the proportions-adjustment methods inverted TIV-VOIs relationships and resulted in larger adjusted volumes in females, promoting sex differences largely attributable to TIV variation and very distinct from those observed in the TIV-matched subsample. The other three methods provided results unrelated to TIV and very similar to those of the TIV-matched subsample. In these datasets, sex differences were bidirectional and achieved satisfactory replication rates in 19 VOIs, but they were "small" (d?

SUBMITTER: Sanchis-Segura C

PROVIDER: S-EPMC6604149 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Sex differences in gray matter volume: how many and how large are they really?

Sanchis-Segura Carla C Ibañez-Gual Maria Victoria MV Adrián-Ventura Jesús J Aguirre Naiara N Gómez-Cruz Álvaro Javier ÁJ Avila César C Forn Cristina C

Biology of sex differences 20190701 1

<h4>Background</h4>Studies assessing volumetric sex differences have provided contradictory results. Total intracranial volume (TIV) is a major confounding factor when estimating local volumes of interest (VOIs). We investigated how the number, size, and direction of sex differences in gray matter volume (GMv) vary depending on how TIV variation is statistically handled.<h4>Methods</h4>Sex differences in the GMv of 116 VOIs were assessed in 356 participants (171 females) without correcting for T ...[more]

PMID: 31262342

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Project description:Developmental structural neuroimaging studies in humans have long described decreases in gray matter volume (GMV) and cortical thickness (CT) during adolescence. Gray matter density (GMD), a measure often assumed to be highly related to volume, has not been systematically investigated in development. We used T1 imaging data collected on the Philadelphia Neurodevelopmental Cohort to study age-related effects and sex differences in four regional gray matter measures in 1189 youths ranging in age from 8 to 23 years. Custom T1 segmentation and a novel high-resolution gray matter parcellation were used to extract GMD, GMV, gray matter mass (GMM; defined as GMD × GMV), and CT from 1625 brain regions. Nonlinear models revealed that each modality exhibits unique age-related effects and sex differences. While GMV and CT generally decrease with age, GMD increases and shows the strongest age-related effects, while GMM shows a slight decline overall. Females have lower GMV but higher GMD than males throughout the brain. Our findings suggest that GMD is a prime phenotype for the assessment of brain development and likely cognition and that periadolescent gray matter loss may be less pronounced than previously thought. This work highlights the need for combined quantitative histological MRI studies.SIGNIFICANCE STATEMENT This study demonstrates that different MRI-derived gray matter measures show distinct age and sex effects and should not be considered equivalent but complementary. It is shown for the first time that gray matter density increases from childhood to young adulthood, in contrast with gray matter volume and cortical thickness, and that females, who are known to have lower gray matter volume than males, have higher density throughout the brain. A custom preprocessing pipeline and a novel high-resolution parcellation were created to analyze brain scans of 1189 youths collected as part of the Philadelphia Neurodevelopmental Cohort. A clear understanding of normal structural brain development is essential for the examination of brain-behavior relationships, the study of brain disease, and, ultimately, clinical applications of neuroimaging.

Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Project description:Introduction: Adolescent-onset cannabis use is rising in the era of marijuana legalization. Recent imaging studies have identified neuroanatomical differences between adult cannabis users and controls that are more prominent in early-onset users. Other studies point to sex-dependent effects of cannabis. Methods: A systematic review following PRISMA guidelines and subsequent effect-size seed-based d mapping (SDM) meta-analyses were conducted to investigate relationships between age (across the 12-to-21-year-old developmental window), sex, and gray matter volume (GMV) differences between cannabis using (CU) and typically developing (TD) youth. Results: Our search identified 1,326 citations, 24 of which were included in a qualitative analysis. A total of 6 whole-brain voxel-based morphometry (VBM) studies comparing regional GMV between 357 CU [mean (SD) age = 16.68 (1.28); 71% male] and 404 TD [mean (SD) age = 16.77 (1.36); 63% male] youth were included in the SDM-meta-analysis. Meta-analysis of whole-brain VBM studies identified no regions showing significant GMV difference between CU and TD youth. Meta-regressions showed divergent effects of age and sex on cortical GMV differences in CU vs. TD youth. Age effects were seen in the superior temporal gyrus (STG), with older-aged CU youth showing decreased and younger-aged CU youth showing increased STG GMV compared to age-matched TD youth. Parallel findings in the STG were also observed in relation to duration of CU (years) in supplemental meta-regressions. Regarding sex effects, a higher proportion of females in studies was associated with increased GMV in the middle occipital gyrus in CU vs. TD youth. Conclusions: These findings suggest that GMV differences between CU and TD youth, if present, are subtle, and may vary as a function of age, cumulative cannabis exposure, and sex in young people. Whether age- and sex-related GMV differences are attributable to common predispositional factors, cannabis-induced neuroadaptive changes, or both warrant further investigation.

Dataset Information

Sex differences in gray matter volume: how many and how large are they really?

Publications

Sex differences in gray matter volume: how many and how large are they really?

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