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A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required., (© 2024. The Author(s).)

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer., Competing Interests: Declaration of interests H.H. and I.C.H. received funding from Alzheimer’s Research UK and the Dunhill Medical Trust Foundation. M.A.P. reported receiving grants and personal and travel fees from Roche, Novartis, Merck, and Biogen outside the submitted work. M. Scholz receives funding from Pfizer Inc. for a project not related to this research. C.D. serves as a consultant of Novartis Pharmaceuticals. B.F. has received educational speaking fees from Medice. N.J. and P.M.T. are MPIs of a research grant from Biogen Inc. for work unrelated to the contents of this manuscript. D.J.W. received funding from the Stroke Foundation/British Heart Foundation. D.J.S. has received consultancy honoraria from Discovery Vitality, Johnson & Johnson, Kanna, L’Oreal, Lundbeck, Orion, Sanofi, Servier, Takeda, and Vistagen. H.H. received funding from MRC, Wellcome Trust, and NIHR UCLH BRC. H.J.G. has received travel grants and speaker’s honoraria from Fresenius Medical Care, Neuraxpharm, and Janssen Cilag as well as research funding from Fresenius Medical Care., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns ( n  = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders., Competing Interests: The authors declare no competing interests.

Structural brain imaging parameters may successfully predict cognitive performance in neurodegenerative diseases but mostly fail to predict cognitive abilities in healthy older adults. One important aspect contributing to this might be sex differences. Behaviorally, older males and females have been found to differ in terms of cognitive profiles, which cannot be captured by examining them as one homogenous group. In the current study, we examined whether the prediction of cognitive performance from brain structure, i.e. region-wise grey matter volume (GMV), would benefit from the investigation of sex-specific cognitive profiles in a large sample of older adults (1000BRAINS; N = 634; age range 55-85 years). Prediction performance was assessed using a machine learning (ML) approach. Targets represented a) a whole-sample cognitive component solution extracted from males and females, and b) sex-specific cognitive components. Results revealed a generally low predictability of cognitive profiles from region-wise GMV. In males, low predictability was observed across both, the whole sample as well as sex-specific cognitive components. In females, however, predictability differences across sex-specific cognitive components were observed, i.e. visual working memory (WM) and executive functions showed higher predictability than fluency and verbal WM. Hence, results accentuated that addressing sex-specific cognitive profiles allowed a more fine-grained investigation of predictability differences, which may not be observable in the prediction of the whole-sample solution. The current findings not only emphasize the need to further investigate the predictive power of each cognitive component, but they also emphasize the importance of sex-specific analyses in older adults., (© 2023. The Author(s).)

Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML). Thus, the aim of the current study was to investigate the general validity of cognitive performance prediction from imaging data in healthy older adults. In particular, the focus was with examining whether (1) multimodal information, i.e., region-wise grey matter volume (GMV), resting-state functional connectivity (RSFC), and structural connectivity (SC) estimates, may improve predictability of cognitive targets, (2) predictability differences arise for global cognition and distinct cognitive profiles, and (3) results generalize across different ML approaches in 594 healthy older adults (age range: 55-85 years) from the 1000BRAINS study. Prediction potential was examined for each modality and all multimodal combinations, with and without confound (i.e., age, education, and sex) regression across different analytic options, i.e., variations in algorithms, feature sets, and multimodal approaches (i.e., concatenation vs. stacking). Results showed that prediction performance differed considerably between deconfounding strategies. In the absence of demographic confounder control, successful prediction of cognitive performance could be observed across analytic choices. Combination of different modalities tended to marginally improve predictability of cognitive performance compared to single modalities. Importantly, all previously described effects vanished in the strict confounder control condition. Despite a small trend for a multimodal benefit, developing a biomarker for cognitive aging remains challenging., (© 2023. The Author(s).)

Background: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure., Methods: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference., Results: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness., Conclusions: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment., (Copyright © 2023. Published by Elsevier Inc.)

The mechanisms of cognitive decline and its variability during healthy aging are not fully understood, but have been associated with reorganization of white matter tracts and functional brain networks. Here, we built a brain network modeling framework to infer the causal link between structural connectivity and functional architecture and the consequent cognitive decline in aging. By applying in-silico interhemispheric degradation of structural connectivity, we reproduced the process of functional dedifferentiation during aging. Thereby, we found the global modulation of brain dynamics by structural connectivity to increase with age, which was steeper in older adults with poor cognitive performance. We validated our causal hypothesis via a deep-learning Bayesian approach. Our results might be the first mechanistic demonstration of dedifferentiation during aging leading to cognitive decline., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2023. Published by Elsevier Inc.)

Background: Bilingualism is associated with higher gray matter volume (GMV) as a form of brain reserve in brain regions such as the inferior frontal gyrus (IFG) and the inferior parietal lobule (IPL). A recent cross-sectional study reported the age-related GMV decline in the left IFG and IPL to be steeper for bilinguals than for monolinguals. The present study aimed at supporting this finding for the first time with longitudinal data., Methods: In the current study, 200 participants aged 19 to 79 years (87 monolinguals, 113 sequential bilinguals, mostly native German speakers with variable second language background) were included. Trajectories of GMV decline in the bilateral IFG and IPL were analyzed in mono- and bilinguals over two time points (mean time interval: 3.6 years). For four regions of interest (left/right IFG and left/right IPL), mixed Analyses of Covariance were conducted to assess (i) GMV changes over time, (ii) GMV differences for language groups (monolinguals/bilinguals), and (iii) the interaction between time point and language group. Corresponding analyses were conducted for the two factors of GMV, surface area (SA) and cortical thickness (CT)., Results: There was higher GMV in bilinguals compared to monolinguals in the IPL, but not IFG. While the left and right IFG and the right IPL displayed a similar GMV change in mono- and bilinguals, GMV decline within the left IPL was significantly steeper in bilinguals. There was greater SA in bilinguals in the bilateral IPL and a steeper CT decline in bilinguals within in the left IPL., Conclusion: The cross-sectional observations of a steeper GMV decline in bilinguals could be confirmed for the left IPL. Additionally, the higher GMV in bilinguals in the bilateral IPL may indicate that bilingualism contributes to brain reserve especially in posterior brain regions. SA appeared to contribute to bilinguals' higher GMV in the bilateral IPL, while CT seemed to account for the steeper structural decline in bilinguals in the left IPL. The present findings demonstrate the importance of time as an additional factor when assessing the neuroprotective effects of bilingualism on structural features of the human brain., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Peitz, Stumme, Jockwitz, Bittner, Caspers and Heim.)

Background: White matter hyperintensities of presumed vascular origin (WMH) are frequent in cerebral magnetic resonance imaging of older people. They are promoted by vascular risk factors, especially hypertension, and are associated with cognitive deficits at the group level. It has been suggested that not only the severity, but also the location, of lesions might critically influence cognitive deficits and represent different pathologies., Methods: In 560 participants (65.2 ± 7.5 years, 51.4% males) of the population-based 1000BRAINS study, we analyzed the association of regional WMH using Fazekas scoring separately for cerebral lobes, with hypertension and cognition., Results: WMH most often affected the frontal lobe (83.7% score >0), followed by the parietal (75.8%), temporal (32.7%), and occipital lobe (7.3%). Higher Fazekas scores in the frontal, parietal, and temporal lobe were associated with higher blood pressure and antihypertensive treatment in unadjusted ordinal regression models and in models adjusted for age, sex, and vascular risk factors (e.g., age- and sex-adjusted odds ratio = 1.14, 95% confidence interval = 1.03-1.25 for the association of frontal lobe WMH Fazekas score with systolic blood pressure [SBP] [per 10 mm Hg]; 1.13 [1.02-1.23] for the association of parietal lobe score with SBP; 1.72 [1.19-2.48] for the association of temporal lobe score with antihypertensive medications). In linear regressions, higher frontal lobe scores were associated with lower performance in executive function and non-verbal memory, and higher parietal lobe scores were associated with lower performance in executive function, verbal-, and non-verbal memory., Conclusions: Hypertension promotes WMH in the frontal, parietal, and temporal lobe. WMH in the frontal and parietal lobe are associated with reduced executive function and memory., (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Age-related cognitive decline varies greatly in healthy older adults, which may partly be explained by differences in the functional architecture of brain networks. Resting-state functional connectivity (RSFC) derived network parameters as widely used markers describing this architecture have even been successfully used to support diagnosis of neurodegenerative diseases. The current study aimed at examining whether these parameters may also be useful in classifying and predicting cognitive performance differences in the normally aging brain by using machine learning (ML). Classifiability and predictability of global and domain-specific cognitive performance differences from nodal and network-level RSFC strength measures were examined in healthy older adults from the 1000BRAINS study (age range: 55-85 years). ML performance was systematically evaluated across different analytic choices in a robust cross-validation scheme. Across these analyses, classification performance did not exceed 60% accuracy for global and domain-specific cognition. Prediction performance was equally low with high mean absolute errors ( MAE s ≥ 0.75) and low to none explained variance ( R 2 ≤ 0.07) for different cognitive targets, feature sets, and pipeline configurations. Current results highlight limited potential of functional network parameters to serve as sole biomarker for cognitive aging and emphasize that predicting cognition from functional network patterns may be challenging., (© 2022 Massachusetts Institute of Technology.)

The angular gyrus (AG) has been associated with multiple cognitive functions, such as language, spatial and memory functions. Since the AG is thought to be a cross-modal hub region suffering from significant age-related structural atrophy, it may also play a key role in age-related cognitive decline. However, the exact relation between structural atrophy of the AG and cognitive decline in older adults is not fully understood, which may be related to two aspects: First, the AG is cytoarchitectonically divided into two areas, PGa and PGp, potentially sub-serving different cognitive functions. Second, the older adult population is characterized by high between-subjects variability which requires targeting individual phenomena during the aging process. We therefore performed a multimodal (gray matter volume [GMV], resting-state functional connectivity [RSFC] and structural connectivity [SC]) characterization of AG subdivisions PGa and PGp in a large older adult population, together with relations to age, cognition and lifestyle on the group level. Afterwards, we switched the perspective to the individual, which is especially important when it comes to the assessment of individual patients. The AG can be considered a heterogeneous structure in of the older brain: we found the different AG parts to be associated with different patterns of whole-brain GMV associations as well as their associations with RSFC, and SC patterns. Similarly, differential effects of age, cognition and lifestyle on the GMV of AG subdivisions were observed. This suggests each region to be structurally and functionally differentially involved in the older adult's brain network architecture, which was supported by differential molecular and genetic patterns, derived from the EBRAINS multilevel atlas framework. Importantly, individual profiles deviated considerably from the global conclusion drawn from the group study. Hence, general observations within the older adult population need to be carefully considered, when addressing individual conditions in clinical practice., (© 2022. The Author(s).)

In the normal aging process, the functional connectome restructures and shows a shift from more segregated to more integrated brain networks, which manifests itself in highly different cognitive performances in older adults. Underpinnings of this reorganization are not fully understood, but may be related to age-related differences in structural connectivity, the underlying scaffold for information exchange between regions. The structure-function relationship might be a promising factor to understand the neurobiological sources of interindividual cognitive variability, but remain unclear in older adults. Here, we used diffusion weighted and resting-state functional magnetic resonance imaging as well as cognitive performance data of 573 older subjects from the 1000BRAINS cohort (55-85 years, 287 males) and performed a partial least square regression on 400 regional functional and structural connectivity (FC and SC, respectively) estimates comprising seven resting-state networks. Our aim was to identify FC and SC patterns that are, together with cognitive performance, characteristic of the older adults aging process. Results revealed three different aging profiles prevalent in older adults. FC was found to behave differently depending on the severity of age-related SC deteriorations. A functionally highly interconnected system is associated with a structural connectome that shows only minor age-related decreases. Because this connectivity profile was associated with the most severe age-related cognitive decline, a more interconnected FC system in older adults points to a process of dedifferentiation. Thus, functional network integration appears to increase primarily when SC begins to decline, but this does not appear to mitigate the decline in cognitive performance., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Objectives: White matter hyperintensities (WMH) of presumed vascular origin are frequent in cerebral MRI of older people. They represent a sign of small vessel disease, are promoted by arterial hypertension, and relate to cognitive deficits. The interdependence of blood pressure and its treatment, WMH, and cognitive performance has not systematically been studied in population-based studies., Methods: Consequently, we analysed the interdependence of SBP, DBP, and antihypertensive medications, as well as BP/treatment category, with WMH and cognitive performance in 560 participants of the population-based 1000BRAINS study., Results: BP, its treatment, and BP/treatment category were moderately associated with cognitive performance (e.g. unadjusted β  = -0.10, 95%CI = -0.19 to -0.02 for the association of SBP (per standard deviation of 17.2 mmHg) with global cognition (per standard deviation of 0.5 z score)]. The harmful effect of BP on cognition was strongly mediated by periventricular hyperintensities (PVH), which were significantly associated with both SBP [ β  = 0.24, 95% CI = 0.14-0.34 (per 1-point-increase in Fazekas score)] and global cognition ( β  = -0.22, 95%CI =  -0.32 to -0.13). Thus, PVH mediated as much as 52% of the effects of SBP on cognitive performance. Mediation was less strong for deep white matter hyperintensities (DWMH, 16%), which showed less association with SBP ( β  = 0.14, 95% CI = 0.05-0.24) and global cognition ( β  = -0.12, 95%CI = -0.21 to -0.03). Regarding different cognitive domains, PVH most strongly mediated effects of SBP on nonverbal memory (94%) and executive function (81%)., Conclusion: Our results indicate that PVH may predispose to cognitive impairment associated with hypertension, especially in the domains of nonverbal memory and executive function., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown., Objective: This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks., Methods: Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter ( PM 10 , PM 2.5 , and PM 2.5 absorbance), accumulation mode particle number ( PN AM ), and nitrogen dioxide ( NO 2 ) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h ( L den ) and nighttime ( L night ) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables., Results: Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, - 0.006 (95% CI: - 0.021 , 0.009) per 0.3 × 10 - 5 / m increase in PM 2.5 absorbance and - 0.004 (95% CI: - 0.006 , - 0.002 ) per 1-y age increase]., Conclusion: High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Neuropsychological studies reported that shift workers show reduced cognitive performance and circadian dysfunctions which may impact structural and functional brain networks. Here we tested the hypothesis whether night shift work is associated with resting-state functional connectivity (RSFC), cortical thickness and gray matter volume in participants of the 1000BRAINS study for whom information on night shift work and imaging data were available. 13 PRESENT and 89 FORMER night shift workers as well as 430 control participants who had never worked in shift (NEVER) met these criteria and were included in our study. No associations between night shift work, three graph-theoretical measures of RSFC of 7 functional brain networks and brain morphology were found after multiple comparison correction. Preceding multiple comparison correction, our results hinted at an association between more years of shift work and higher segregation of the visual network in PRESENT shift workers and between shift work experience and lower gray matter volume of the left thalamus. Extensive neuropsychological investigations supplementing objective imaging methodology did not reveal an association between night shift work and cognition after multiple comparison correction. Our pilot study suggests that night shift work does not elicit general alterations in brain networks and affects the brain only to a limited extent. These results now need to be corroborated in studies with larger numbers of participants., (© 2022. The Author(s).)

Background: While evidence suggests that long-term air pollution (AP) and noise may adversely affect cognitive function, little is known about whether environmental exposures also promote structural changes in underlying brain networks. We therefore investigated the associations between AP, traffic noise, and structural measures of the Default Mode Network (DMN), a functional brain network known to undergo specific changes with age., Methods: We analyzed data from 579 participants (mean age at imaging: 66.5 years) of the German 1000BRAINS study. Long-term residential exposure to particulate matter (diameter ≤10 μm [PM 10 ]; diameter ≤2.5 μm [PM 2.5 ]), PM 2.5 absorbance (PM 2.5abs ), nitrogen dioxide (NO 2 ), and accumulation mode particulate number concentration (PN AM ) was estimated using validated land use regression and chemistry transport models. Long-term outdoor traffic noise was modeled at participants' homes based on a European Union's Environmental Noise Directive. As measures of brain structure, cortical thickness and local gyrification index (lGI) values were calculated for DMN regions from T1-weighted structural brain images collected between 2011 and 2015. Associations between environmental exposures and brain structure measures were estimated using linear regression models, adjusting for demographic and lifestyle characteristics., Results: AP exposures were below European Union standards but above World Health Organization guidelines (e.g., PM 10 mean: 27.5 μg/m 3 ). A third of participants experienced outdoor 24-h noise above European recommendations. Exposures were not consistently associated with lGI values in the DMN. We observed weak inverse associations between AP and cortical thickness in the right anterior DMN (e.g., -0.010 mm [-0.022, 0.002] per 0.3 unit increase in PM 2.5abs ) and lateral part of the posterior DMN., Conclusion: Long-term AP and noise were not consistently associated with structural parameters of the DMN in the brain. While weak associations were present between AP exposure and cortical thinning of right hemispheric DMN regions, it remains unclear whether AP might influence DMN brain structure in a similar way as aging., (Copyright © 2021 Elsevier GmbH. All rights reserved.)

[Figure: see text].

Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults ( n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jockwitz, Mérillat, Liem, Oschwald, Amunts, Jäncke and Caspers.)

Lifestyle may be one source of unexplained variance in the great interindividual variability of the brain in age-related structural differences. While physical and social activity may protect against structural decline, other lifestyle behaviors may be accelerating factors. We examined whether riskier lifestyle correlates with accelerated brain aging using the BrainAGE score in 622 older adults from the 1000BRAINS cohort. Lifestyle was measured using a combined lifestyle risk score, composed of risk (smoking, alcohol intake) and protective variables (social integration and physical activity). We estimated individual BrainAGE from T1-weighted MRI data indicating accelerated brain atrophy by higher values. Then, the effect of combined lifestyle risk and individual lifestyle variables was regressed against BrainAGE. One unit increase in combined lifestyle risk predicted 5.04 months of additional BrainAGE. This prediction was driven by smoking (0.6 additional months of BrainAGE per pack-year) and physical activity (0.55 less months in BrainAGE per metabolic equivalent). Stratification by sex revealed a stronger association between physical activity and BrainAGE in males than females. Overall, our observations may be helpful with regard to lifestyle-related tailored prevention measures that slow changes in brain structure in older adults.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

The hippocampus is a plastic region and highly susceptible to ageing and dementia. Previous studies explicitly imposed a priori models of hippocampus when investigating ageing and dementia-specific atrophy but led to inconsistent results. Consequently, the basic question of whether macrostructural changes follow a cytoarchitectonic or functional organization across the adult lifespan and in age-related neurodegenerative disease remained open. The aim of this cross-sectional study was to identify the spatial pattern of hippocampus differentiation based on structural covariance with a data-driven approach across structural MRI data of large cohorts (n = 2594). We examined the pattern of structural covariance of hippocampus voxels in young, middle-aged, elderly, mild cognitive impairment and dementia disease samples by applying a clustering algorithm revealing differentiation in structural covariance within the hippocampus. In all the healthy and in the mild cognitive impaired participants, the hippocampus was robustly divided into anterior, lateral and medial subregions reminiscent of cytoarchitectonic division. In contrast, in dementia patients, the pattern of subdivision was closer to known functional differentiation into an anterior, body and tail subregions. These results not only contribute to a better understanding of co-plasticity and co-atrophy in the hippocampus across the lifespan and in dementia, but also provide robust data-driven spatial representations (i.e. maps) for structural studies., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Healthy aging has been associated with a decrease in functional network specialization. Importantly, variability of alterations of functional connectivity is especially high across older adults. Whole-brain functional network reorganization, though, and its impact on cognitive performance within particularly the older generation is still a matter of debate. We assessed resting state functional connectivity (RSFC) in 772 older adults (55-85 years, 421 males) using a graph-theoretical approach. Results show overall age-related increases of between- and decreases of within-network RSFC. With similar phenomena observed in young to middle-aged adults, i.e. that RSFC reorganizes towards more pronounced functional network integration, the current results amend such evidence for the old age. The results furthermore indicate that RSFC reorganization in older adults particularly pertain to early sensory networks (e.g. visual and sensorimotor network). Importantly, RSFC differences of these early sensory networks were found to be a relevant mediator in terms of the age-related cognitive performance differences. Further, we found systematic sex-related network differences with females showing patterns of more segregation (i.e. default mode and ventral attention network) and males showing a higher integrated network system (particularly for the sensorimotor network). These findings underpin the notion of sex-related connectivity differences, possibly facilitating sex-related behavioral functioning., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Despite the importance of understanding associations of air pollution and noise exposure with loss of neurocognitive performance, studies investigating these exposures and local brain structure are limited., Objective: We estimated associations of residential air pollution and noise exposures with neurocognitive test performance and the local gyrification index (lGI), a marker for local brain atrophy, among older adults., Methods: For n = 615 participants from the population-based 1000BRAINS study, based on the German Heinz Nixdorf Recall study, we assessed residential exposures to particulate matter ( PM 10 , PM 2.5 , PM 2.5 abs ), accumulation mode particle number ( PN AM ), and nitrogen oxides ( NO x , NO 2 ), using land-use regression and chemistry transport models. Weighted 24-h and nighttime noise were modeled according to the European noise directive. We evaluated associations of air pollution and noise exposure at the participants' 2006-2008 residential addresses with neurocognitive test performance and region-specific lGI values ( n = 590 ) from magnetic resonance imaging, both assessed in 2011-2015, using linear regression and adjusting for demographic and personal characteristics., Results: Air pollution and noise were associated with language and short-term/working memory and with local atrophy of the fronto-parietal network (FPN), a functional resting-state network associated with these cognitive processes. For example, per 2 - μ g / m 3 PM 10 , local brain atrophy was more pronounced in the posterior brain regions of the FPN, with a - 0.02 [95% confidence interval (CI): - 0.04 , 0.00] lower lGI. In contrast, in the anterior regions of the FPN, weighted 24-h and nighttime noise were associated with less local brain atrophy [e.g., 0.02 (95% CI: 0.00, 0.04) for 10  dB (A) 24-h noise]., Conclusions: Air pollution and noise exposures were associated in opposite directions with markers of local atrophy of the FPN in the right brain hemisphere in older adults, suggesting that both chronic air pollution and noise exposure may influence the physiological aging process of the brain. https://doi.org/10.1289/EHP5859.

Importance: Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., Objective: To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., Design, Setting, and Participants: In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., Main Outcomes and Measures: The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., Results: Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., Conclusions and Relevance: These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.

Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic factors may influence both aging and disease. Here we focused on this issue and investigated effects of multiple genetic loci previously identified to be associated with late-onset Alzheimer's disease (AD) on brain structure of older adults from a population sample. We calculated a genetic risk score (GRS) using genome-wide significant single-nucleotide polymorphisms from genome-wide association studies of AD and tested its effect on cortical thickness (CT). We observed a common pattern of cortical thinning (right inferior frontal, left posterior temporal, medial occipital cortex). To identify CT changes by specific biological processes, we subdivided the GRS effect according to AD-associated pathways and performed follow-up analyses. The common pattern from the main analysis was further differentiated by pathway-specific effects yielding a more bilateral pattern. Further findings were located in the superior parietal and mid/anterior cingulate regions representing 2 unique pathway-specific patterns. All patterns, except the superior parietal pattern, were influenced by apolipoprotein E. Our step-wise approach revealed atrophy patterns that partially resembled imaging findings in early stages of AD. Our study provides evidence that genetic burden for AD contributes to structural brain variability in normal aging., (© The Author(s) 2019. Published by Oxford University Press.)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)