Surface area of the cerebral cortex is a highly heritable trait, yet little is known about genetic influences on regional cortical differentiation in humans. Using a data-driven, fuzzy clustering ...technique with magnetic resonance imaging data from 406 twins, we parceled cortical surface area into genetic subdivisions, creating a human brain atlas based solely on genetically informative data. Boundaries of the genetic divisions corresponded largely to meaningful structural and functional regions; however, the divisions represented previously undescribed phenotypes different from conventional (non-genetically based) parcellation systems. The genetic organization of cortical area was hierarchical, modular, and predominantly bilaterally symmetric across hemispheres. We also found that the results were consistent with human-specific regions being subdivisions of previously described, genetically based lobar regionalization patterns.
Animal data demonstrate that the development of distinct cortical areas is influenced by genes that exhibit highly regionalized expression patterns. In this paper, we show genetic patterning of ...cortical surface area derived from MRI data from 406 adult human twins. We mapped genetic correlations of areal expansion between selected seed regions and all other cortical locations, with the selection of seed points based on results from animal studies. “Marching seeds” and a data-driven, hypothesis-free, fuzzy-clustering approach provided convergent validation. The results reveal strong anterior-to-posterior graded, bilaterally symmetric patterns of regionalization, largely consistent with patterns previously reported in nonhuman mammalian models. Broad similarities in genetic patterning between rodents and humans might suggest a conservation of cortical patterning mechanisms, whereas dissimilarities might reflect the functionalities most essential to each species.
► Overall genetic regionalization in humans reflects general mammalian patterning ► The patterns are largely bilaterally symmetric and correspond to lobar divisions ► There are also regionalization differences consistent with species-specific features ► The genetic patterns of the cortical surface area and thickness are different
Genetic topography of brain morphology Chen, Chi-Hua; Fiecas, Mark; Gutierrez, E. D. ...
Proceedings of the National Academy of Sciences - PNAS,
10/2013, Letnik:
110, Številka:
42
Journal Article
Recenzirano
Odprti dostop
Animal data show that cortical development is initially patterned by genetic gradients largely along three orthogonal axes. We previously reported differences in genetic influences on cortical ...surface area along an anterior-posterior axis using neuroimaging data of adult human twins. Here, we demonstrate differences in genetic influences on cortical thickness along a dorsal-ventral axis in the same cohort. The phenomenon of orthogonal gradations in cortical organization evident in different structural and functional properties may originate from genetic gradients. Another emerging theme of cortical patterning is that patterns of genetic influences recapitulate the spatial topography of the cortex within hemispheres. The genetic patterning of both cortical thickness and surface area corresponds to cortical functional specializations. Intriguingly, in contrast to broad similarities in genetic patterning, two sets of analyses distinguish cortical thickness and surface area genetically. First, genetic contributions to cortical thickness and surface area are largely distinct; there is very little genetic correlation (i.e., shared genetic influences) between them. Second, organizing principles among genetically defined regions differ between thickness and surface area. Examining the structure of the genetic similarity matrix among clusters revealed that, whereas surface area clusters showed great genetic proximity with clusters from the same lobe, thickness clusters appear to have close genetic relatedness with clusters that have similar maturational timing. The discrepancies are in line with evidence that the two traits follow different mechanisms in neurodevelopment. Our findings highlight the complexity of genetic influences on cortical morphology and provide a glimpse into emerging principles of genetic organization of the cortex.
Type 2 diabetes has a strong association with the development of cardiovascular disease, which is grouped as diabetic heart disease (DHD). DHD is associated with the progressive loss of ...cardiovascular cells through the alteration of molecular signalling pathways associated with cell death. In this study, we sought to determine whether diabetes induces dysregulation of miR-532 and if this is associated with accentuated apoptosis. RT-PCR analysis showed a significant increase in miR-532 expression in the right atrial appendage tissue of type 2 diabetic patients undergoing coronary artery bypass graft surgery. This was associated with marked downregulation of its anti-apoptotic target protein apoptosis repressor with caspase recruitment domain (ARC) and increased TUNEL positive cardiomyocytes. Further analysis showed a positive correlation between apoptosis and miR-532 levels. Time-course experiments in a mouse model of type 2 diabetes showed that diabetes-induced activation of miR-532 occurs in the later stage of the disease. Importantly, the upregulation of miR-532 preceded the activation of pro-apoptotic caspase-3/7 activity. Finally, inhibition of miR-532 activity in high glucose cultured human cardiomyocytes prevented the downregulation of ARC and attenuated apoptotic cell death. Diabetes induced activation of miR-532 plays a critical role in accelerating cardiomyocytes apoptosis. Therefore, miR-532 may serve as a promising therapeutic agent to overcome the diabetes-induced loss of cardiomyocytes.
Neuroimaging studies examining the effects of aging and neuropsychiatric disorders on the cerebral cortex have largely been based on measures of cortical volume. Given that cortical volume is a ...product of thickness and surface area, it is plausible that measures of volume capture at least 2 distinct sets of genetic influences. The present study aims to examine the genetic relationships between measures of cortical surface area and thickness. Participants were men in the Vietnam Era Twin Study of Aging (110 monozygotic pairs and 92 dizygotic pairs). Mean age was 55.8 years (range: 51–59). Bivariate twin analyses were utilized in order to estimate the heritability of cortical surface area and thickness, as well as their degree of genetic overlap. Total cortical surface area and average cortical thickness were both highly heritable (0.89 and 0.81, respectively) but were essentially unrelated genetically (genetic correlation = 0.08). This pattern was similar at the lobar and regional levels of analysis. These results demonstrate that cortical volume measures combine at least 2 distinct sources of genetic influences. We conclude that using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.
The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 ...MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease).
The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, ...most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individual-specific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study of Aging (VETSA). They were 51–59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00–0.75) as compared with subcortical and ventricular ROIs (0.48–0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.
Subjective memory concern has long been considered a state-related indicator of impending cognitive decline or dementia. The possibility that subjective memory concern may itself be a heritable trait ...is largely ignored, yet such an association would substantially confound its use in clinical or research settings.
To assess the heritability and traitlike dimensions of subjective memory concern and its clinical correlates.
This longitudinal twin cohort study was conducted from 1967 to 2019 among male adults with a mean (SD) age of 37.75 (2.52) years to follow-up at mean ages of 56.15 (2.72), 61.50 (2.43), and 67.35 (2.57) years (hereafter, 38, 56, 62, and 67 years, respectively) in the Vietnam Era Twin Study of Aging. The study included a national community-dwelling sample with health, education, and lifestyle characteristics comparable to a general sample of US men in this age cohort. Participants were monozygotic and dizygotic twins randomly recruited from the Vietnam Era Twin Registry. Data were analyzed from May 2021 to December 2022.
Measures included subjective memory concern at 4 time points; objective memory, depressive symptoms, and anxiety at the last 3 time points; negative emotionality (trait neuroticism) at age 56 years; polygenic risk scores (PRSs) for neuroticism, depression, and Alzheimer disease; APOE genotype; and parental history of dementia. Primary outcomes were heritability and correlations between subjective memory concern and other measures.
The sample included 1555 male adults examined at age 38 years, 520 at age 56 years (due to late introduction of subjective memory concern questions), 1199 at age 62 years, and 1192 at age 67 years. Phenotypically, subjective memory concerns were relatively stable over time. At age 56 years, subjective memory concern had larger correlations with depressive symptoms (r, 0.32; 95% CI, 0.21 to 0.42), anxiety (r, 0.36; 95% CI, 0.18 to 0.51), and neuroticism (r, 0.34; 95% CI, 0.26 to 0.41) than with objective memory (r, -0.24; 95% CI, -0.33 to -0.13). Phenotypic results were similar at ages 62 and 67 years. A best-fitting autoregressive twin model indicated that genetic influences on subjective memory concern accumulated and persisted over time (h2 = 0.26-0.34 from age 38-67 years). At age 56 years, genetic influences for subjective memory concern were moderately correlated with genetic influences for anxiety (r, 0.36; 95% CI, 0.18 to 0.51), negative emotionality (r, 0.51; 95% CI, 0.44-0.57), and depressive symptoms (r, 0.20; 95% CI, 0.10 to 0.29) as well as objective memory (r, -0.22; 95% CI, -0.30 to -0.14). Similar genetic correlations were seen at ages 62 and 67 years. The neuroticism PRS was associated with subjective memory concern at age 38 years (r, 0.10; 95% CI, 0.03. to 0.18) and age 67 years (r, 0.09; 95% CI, 0.01 to 0.16). Subjective memory concern was not associated with any Alzheimer disease risk measures.
This cohort study found stable genetic influences underlying subjective memory concern dating back to age 38 years. Subjective memory concern had larger correlations with affect-related measures than with memory-related measures. Improving the utility of subjective memory concern as an indicator of impending cognitive decline and dementia may depend on isolating its statelike component from its traitlike component.
Total gray matter volume is associated with general cognitive ability (GCA), an association mediated by genetic factors. It is expectable that total neocortical volume should be similarly associated ...with GCA. Neocortical volume is the product of thickness and surface area, but global thickness and surface area are unrelated phenotypically and genetically in humans. The nature of the genetic association between GCA and either of these 2 cortical dimensions has not been examined. Humans possess greater cognitive capacity than other species, and surface area increases appear to be the primary driver of the increased size of the human cortex. Thus, we expected neocortical surface area to be more strongly associated with cognition than thickness. Using multivariate genetic analysis in 515 middle-aged twins, we demonstrated that both the phenotypic and genetic associations between neocortical volume and GCA are driven primarily by surface area rather than thickness. Results were generally similar for each of 4 specific cognitive abilities that comprised the GCA measure. Our results suggest that emphasis on neocortical surface area, rather than thickness, could be more fruitful for elucidating neocortical-GCA associations and identifying specific genes underlying those associations.