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Our understanding of brain iron regulation and its disruption in disease is limited. Excess iron affects motor circuitry, contributing to Parkinson's disease (PD) risk. The molecular mechanisms regulating central iron levels, beyond a few well-known genes controlling peripheral iron, remain unclear. We generated scores based on the archetypal brain iron accumulation observed in magnetic resonance imaging scans of individuals with excessive dietary iron absorption and hemochromatosis risk. Genome-wide analysis revealed that this score is highly heritable, identifying loci associated with iron homeostasis, and driven by peripheral iron levels. Our score predicted gait abnormalities and showed a U-shaped relationship with PD risk, identifying individuals with threefold increased risk. These results establish a hormetic relationship between brain iron and PD risk, where central iron levels are strongly determined by genetics via peripheral iron. This framework combining forward and reverse genetics is a powerful study design to understand genomic drivers underlying high dimensional phenotypes.

BackgroundChronic pain leads to tau accumulation and hippocampal atrophy, which may be moderated through inflammation. In older men, we examined associations of chronic pain with Alzheimer's disease (AD)-related plasma biomarkers and hippocampal volume as moderated by systemic inflammation.MethodsParticipants were men without dementia. Chronic pain was defined as moderate-to-severe pain in 2+ study waves at average ages 56, 62, and 68. At age 68, we measured plasma amyloid-beta (Aβ42, n = 871), Aβ40 (n = 887), total tau (t-tau, n = 841), and neurofilament light chain (NfL, n = 915), and serum high-sensitivity C-reactive protein (hs-CRP, n = 968), a marker of systemic inflammation. A subgroup underwent structural MRI to measure hippocampal volume (n = 385). Analyses adjusted for medical morbidities, depressive symptoms, and opioid use.ResultsChronic pain was related to higher Aβ40 (β = 0.25, p = .009), but hs-CRP was unrelated to AD-related biomarkers (ps > .05). There was a significant interaction such that older men with both chronic pain and higher levels of hs-CRP had higher levels of Aβ42 (β = 0.36, p = .001) and Aβ40 (β = 0.29, p = .003). Chronic pain and hs-CRP did not interact to predict levels of Aβ42/Aβ40, t-tau, or NfL. Furthermore, there were significant interactions such that Aβ42 and Aβ40 were associated with lower hippocampal volume, particularly when levels of hs-CRP were elevated (hs-CRP × Aβ42: β = -0.19, p = .002; hs-CRP × Aβ40: β = -0.21, p = .001), regardless of chronic pain status.ConclusionsChronic pain was associated with higher plasma Aβ, especially when hs-CRP was also elevated. Higher hs-CRP and Aβ levels were both related to smaller hippocampal volumes. Chronic pain, when accompanied by systemic inflammation, may elevate the risk of neurodegeneration in AD-vulnerable regions.

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

BackgroundChildhood disadvantage is a prominent risk factor for cognitive and brain aging. Childhood disadvantage is associated with poorer episodic memory in late midlife and functional and structural brain abnormalities in the default mode network (DMN). Although age-related changes in DMN are associated with episodic memory declines in older adults, it remains unclear if childhood disadvantage has an enduring impact on this later-life brain-cognition relationship earlier in the aging process. Here, within the DMN, we examined whether its cortical microstructural integrity-an early marker of structural vulnerability that increases the risk for future cognitive decline and neurodegeneration-is associated with episodic memory in adults at ages 56-66, and whether childhood disadvantage moderates this association.MethodsCortical mean diffusivity (MD) obtained from diffusion magnetic resonance imaging was used to measure microstructural integrity in 350 community-dwelling men. We examined both visual and verbal episodic memory in relation to DMN MD and divided participants into disadvantaged and nondisadvantaged groups based on parental education and occupation.ResultsHigher DMN MD was associated with poorer visual memory but not verbal memory (β = -0.11, p = .040 vs β = -0.04, p = .535). This association was moderated by childhood disadvantage and was significant only in the disadvantaged group (β = -0.26, p = .002 vs β = -0.00, p = .957).ConclusionsLower DMN cortical microstructural integrity may reflect visual memory vulnerability in cognitively normal adults earlier in the aging process. Individuals who experienced childhood disadvantage manifested greater vulnerability to cortical microstructure-related visual memory dysfunction than their nondisadvantaged counterparts who exhibited resilience in the face of low cortical microstructural integrity.

BackgroundPlasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations.MethodsWe examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter.ResultsAfter adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals.ConclusionsThese results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.

BACKGROUND: Increased exposure to ambient air pollution, especially fine particulate matter [less than or equal to]2.5 [micro]m ([PM.sub.2.5]) is associated with poorer brain health and increased risk for Alzheimer's disease (AD) and related dementias. The locus coeruleus (LC), located in the brainstem, is one of the earliest regions affected by tau pathology seen in AD. Its diffuse projections throughout the brain include afferents to olfactory areas that are hypothesized conduits of cerebral particle deposition. Additionally, extensive contact of the LC with the cerebrovascular system may present an additional route of exposure to environmental toxicants. OBJECTIVE: Our aim was to investigate if exposure to [PM.sub.2.5] was associated with LC integrity in a nationwide sample of men in early old age, potentially representing one pathway through which air pollution can contribute to increased risk for AD dementia. METHODS: We examined the relationship between [PM.sub.2.5] and in vivo magnetic resonance imaging (MRI) estimates of LC structural integrity indexed by contrast to noise ratio ([LC.sub.CNR]) in 381 men [mean age = 67.3; standard deviation (SD) = 2.6] from the Vietnam Era Twin Study of Aging (VETSA). Exposure to [PM.sub.2.5] was taken as a 3-year average over the most recent period for which data were available (average of 5.6 years prior to the MRI scan). We focused on [LC.sub.CNR] in the rostral-middle portion of LC due to its stronger associations with aging and AD than the caudal LC. Associations between [PM.sub.2.5] exposures and LC integrity were tested using linear mixed effects models adjusted for age, scanner, education, household income, and interval between exposure and MRI. A co-twin control analysis was also performed to investigate whether associations remained after controlling for genetic confounding and rearing environment. RESULTS: Multiple linear regressions revealed a significant association between [PM.sub.2.5] and rostral-middle [LC.sub.CNR] (b = -0.16; p = 0.02), whereby higher exposure to [PM.sub.2.5] was associated with lower [LC.sub.CNR]. A co-twin control analysis found that, within monozygotic pairs, individuals with higher [PM.sub.2.5] exposure showed lower [LC.sub.CNR] (b = - 0.11; p = 0.02), indicating associations were not driven by genetic or shared environmental confounds. There were no associations between [PM.sub.2.5] and caudal [LC.sub.CNR] or hippocampal volume, suggesting a degree of specificity to the rostral-middle portion of the LC. DISCUSSION: Given previous findings that loss of LC integrity is associated with increased accumulation of AD-related amyloid and tau pathology, impacts on LC integrity may represent a potential pathway through which exposure to air pollution increases AD risk. https://doi.org/10.1289/EHP14344, Introduction Neuropathological studies indicate that abnormal tau may first appear in the locus coeruleus (LC) starting early in life, (1,2) with substantial accumulation occurring during the course of Alzheimer's disease [...]

ObjectivesAbnormal tau, a hallmark Alzheimer's disease (AD) pathology, may appear in the locus coeruleus (LC) decades before AD symptom onset. Reports of subjective cognitive decline are also often present prior to formal diagnosis. Yet, the relationship between LC structural integrity and subjective cognitive decline has remained unexplored. Here, we aimed to explore these potential associations.MethodsWe examined 381 community-dwelling men (mean age = 67.58; SD = 2.62) in the Vietnam Era Twin Study of Aging who underwent LC-sensitive magnetic resonance imaging and completed the Everyday Cognition scale to measure subjective cognitive decline along with their selected informants. Mixed models examined the associations between rostral-middle and caudal LC integrity and subjective cognitive decline after adjusting for depressive symptoms, physical morbidities, and family. Models also adjusted for current objective cognitive performance and objective cognitive decline to explore attenuation.ResultsFor participant ratings, lower rostral-middle LC contrast to noise ratio (LCCNR) was associated with significantly greater subjective decline in memory, executive function, and visuospatial abilities. For informant ratings, lower rostral-middle LCCNR was associated with significantly greater subjective decline in memory only. Associations remained after adjusting for current objective cognition and objective cognitive decline in respective domains.ConclusionsLower rostral-middle LC integrity is associated with greater subjective cognitive decline. Although not explained by objective cognitive performance, such a relationship may explain increased AD risk in people with subjective cognitive decline as the LC is an important neural substrate important for higher order cognitive processing, attention, and arousal and one of the first sites of AD pathology.

Some evidence suggests a biphasic pattern of changes in cortical thickness wherein higher, rather than lower, thickness is associated with very early Alzheimer's disease (AD) pathology. We examined whether integrating information from AD brain signatures based on mean diffusivity (MD) can aid in the interpretation of cortical thickness/volume as a risk factor for future AD-related changes. Participants were 572 men in the Vietnam Era Twin Study of Aging who were cognitively unimpaired at baseline (mean age = 56 years; range = 51-60). Individuals with both high thickness/volume signatures and high MD signatures at baseline had lower cortical thickness/volume in AD signature regions and lower episodic memory performance 12 years later compared to those with high thickness/volume and low MD signatures at baseline. Groups did not differ in level of young adult cognitive reserve. Our findings are in line with a biphasic model in which increased cortical thickness may precede future decline and establish the value of examining cortical MD alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.

BackgroundComposite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown.MethodsOur validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals.ResultsMD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance.ConclusionsCortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns.

Executive function encompasses effortful cognitive processes that are particularly susceptible to aging. Functional brain networks supporting executive function-such as the frontoparietal control network and the multiple demand system-have been extensively investigated. However, it remains unclear how structural networks facilitate and constrain the dynamics of functional networks to contribute to aging-related executive function declines. We examined whether changes in structural network modal controllability-a network's ability to facilitate effortful brain state transitions that support cognitive functions-are associated with changes in executive function cross-sectionally and longitudinally. Diffusion-weighted imaging and neuropsychological testing were conducted at two time points (Time 1: ages 56 to 66, N = 172; Time 2: ages 61 to 70, N = 267) in community-dwelling men from the Vietnam Era Twin Study of Aging. An executive function factor score was computed from six neuropsychological tasks. Structural networks constructed from white matter connectivity were used to estimate modal controllability in control network and multiple demand system. We showed that higher modal controllability in control network and multiple demand system was associated with better executive function at Time 2, after controlling for age, young adult general cognitive ability, and physical health status. Moreover, changes in executive function over a period of 5 to 6 years (Time 1-Time 2, N = 105) were associated with changes in modal controllability of the multiple demand system and weakly in the control network over the same time period. These findings suggest that changes in the ability of structural brain networks in facilitating effortful brain state transitions may be a key neural mechanism underlying aging-related executive function declines and cognitive aging.

BackgroundFine particulate matter (PM2.5) and nitrogen dioxide (NO2) measures of ambient air pollution are associated with accelerated age-related cognitive impairment, and Alzheimer's disease and related dementias (ADRD).ObjectiveWe examined associations between air pollution, four cognitive factors, and the moderating role of apolipoprotein E (APOE) genotype in the understudied period of midlife.MethodsParticipants were ∼1,100 men in the Vietnam Era Twin Study of Aging. Baseline cognitive assessments were from 2003 to 2007. Measures included past (1993-1999) and recent (3 years prior to baseline assessment) PM2.5 and NO2 exposure, in-person assessment of episodic memory, executive function, verbal fluency, and processing speed, and APOE genotype. Average baseline age was 56 years with a 12-year follow-up. Analyses adjusted for health and lifestyle covariates.ResultsPerformance in all cognitive domains declined from age 56 to 68. Higher PM2.5 exposures were associated with worse general verbal fluency. We found significant exposure-by-APOE genotype interactions for specific cognitive domains: PM2.5 with executive function and NO2 with episodic memory. Higher PM2.5 exposure was related to worse executive function in APOE ɛ4 carriers, but not in non-carriers. There were no associations with processing speed.ConclusionThese results indicate negative effects of ambient air pollution exposure on fluency alongside intriguing differential modifications of cognitive performance by APOE genotype. APOE ɛ4 carriers appeared more sensitive to environmental differences. The process by which air pollution and its interaction with genetic risk for ADRD affects risk for later life cognitive decline or progression to dementia may begin in midlife.

The locus coeruleus (LC) is one of the earliest sites of tau pathology, making it a key structure in early Alzheimer's disease (AD) progression. As the primary source of norepinephrine for the brain, reduced LC integrity may have negative consequences for brain health, yet macrostructural brain measures (e.g. cortical thickness) may not be sensitive to early stages of neurodegeneration. We therefore examined whether LC integrity was associated with differences in cortical gray matter microstructure among 435 men (mean age = 67.5; range = 62-71.7). LC structural integrity was indexed by contrast-to-noise ratio (LCCNR) from a neuromelanin-sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi-shell diffusion technique, was used to characterize cortical microstructure, modeling total diffusion in restricted, hindered, and free water compartments. Higher LCCNR (greater integrity) was associated with higher hindered and lower free water diffusion in multiple cortical regions. In contrast, no associations between LCCNR and cortical thickness survived correction. Results suggest lower LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cytoarchitectural barriers due to broader neurodegenerative processes. These findings highlight the potential utility for LC imaging and advanced diffusion measures of cortical microstructure in assessing brain health and early identification of neurodegenerative processes.

Background and aimsSmoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later.DesignProspective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated.SettingPopulation-based United States sample.Participants/casesParticipants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves.MeasurementsSelf-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19).FindingsIn structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD.ConclusionsHeavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.

Influential investigations of postmortem human brain tissue showed regional differences in tissue properties at early phases of development, such as between prefrontal and primary sensory cortical regions. Large-scale neuroimaging studies enable characterization of age-related trajectories with much denser sampling of cortical regions, assessment ages, and demographic variables than postmortem tissue analyses, but no single imaging measure perfectly captures what is measured with histology. Using publicly available data from the Pediatric Imaging, Neurocognition, and Genetics (PING) study, including 951 participants with ages ranging from 3 to 21 years, we characterized cortical regional variability in developmental trajectories of multimodal brain imaging measures. Multivariate analyses integrated morphometric and microstructural cortical surface measures. To replicate foundational histological work showing delayed synapse elimination in middle frontal gyrus relative to primary sensory areas, we tested whether developmental trajectories differ between prefrontal and visual or auditory cortex. We extended this to a whole-cortex analysis of interregional differences, producing cortical parcellations with maximally different developmental trajectories. Consistent with the general conclusions of postmortem analyses, our imaging results suggest that prefrontal regions show a protracted period of greater developmental change; however, they also illustrate the challenges of drawing conclusions about the relative maturational phases of different brain regions.

To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.

During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n = 8086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9-14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes.

Because longitudinal studies of aging typically lack cognitive data from earlier ages, it is unclear how general cognitive ability (GCA) changes throughout the life course. In 1173 Vietnam Era Twin Study of Aging (VETSA) participants, we assessed young adult GCA at average age 20 and current GCA at 3 VETSA assessments beginning at average age 56. The same GCA index was used throughout. Higher young adult GCA and better GCA maintenance were associated with stronger specific cognitive abilities from age 51 to 73. Given equivalent GCA at age 56, individuals who had higher age 20 GCA outperformed those whose GCA remained stable in terms of memory, executive function, and working memory abilities from age 51 to 73. Thus, paradoxically, despite poorer maintenance of GCA, high young adult GCA still conferred benefits. Advanced predicted brain age and the combination of elevated vascular burden and APOE-ε4 status were associated with poorer maintenance of GCA. These findings highlight the importance of distinguishing between peak and current GCA for greater understanding of cognitive aging.

The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.

Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimer's Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 51-72 years. Biometrical genetic analyses "twin models" revealed significant and highly correlated estimates of additive genetic heritability ranging from 59 to 75%. Multivariate longitudinal modeling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences.

We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

[Figure: see text].

Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer's disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Towards that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: (i) a validated MRI-derived Alzheimer's disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and (ii) a novel grey matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246-367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51-60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer's disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61-71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply ageing-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P = 0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step towards improving very early identification of Alzheimer's disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.

IntroductionThe locus coeruleus (LC) undergoes extensive neurodegeneration in early Alzheimer's disease (AD). The LC is implicated in regulating the sleep-wake cycle, modulating cognitive function, and AD progression.MethodsParticipants were 481 men (ages 62 to 71.7) from the Vietnam Era Twin Study of Aging. LC structural integrity was indexed by neuromelanin-sensitive magnetic resonance imaging (MRI) contrast-to-noise ratio (LCCNR ). We examined LCCNR , cognition, amnestic mild cognitive impairment (aMCI), and daytime dysfunction.ResultsHeritability of LCCNR was .48. Participants with aMCI showed greater daytime dysfunction. Lower LCCNR was associated with poorer episodic memory, general verbal fluency, semantic fluency, and processing speed, as well as increased odds of aMCI and greater daytime dysfunction.DiscussionReduced LC integrity is associated with widespread differences across cognitive domains, daytime sleep-related dysfunction, and risk for aMCI. These findings in late-middle-aged adults highlight the potential of MRI-based measures of LC integrity in early identification of AD risk.

Midlife vascular disease increases risk for dementia and effects of vascular dysfunction on brain health differ between men and women. Elevated pulse pressure, a surrogate for arterial stiffness, contributes to cerebrovascular pathology and white matter damage that may advance cognitive aging; however, it remains unclear how associations between pulse pressure and neural integrity differ by sex and age. This study used restriction spectrum imaging to examine associations between pulse pressure and brain microstructure in community-dwelling women (N=88) and men (N=55), aged 56 to 97 (mean, 76.3) years. Restricted isotropic (presumed intracellular), hindered isotropic (presumed extracellular), neurite density, and free water diffusion were computed in white matter tracts and subcortical regions. After adjustment for age and sex, higher pulse pressure correlated with lower restricted isotropic diffusion in global white matter, with more pronounced associations in parahippocampal cingulum, as well as in thalamus and hippocampus. Subgroup analyses demonstrated stronger correlations between pulse pressure and restricted isotropic diffusion in association fibers for participants ≤75 years than for older participants, with stronger effects for women than men of this age group. Microstructure in parahippocampal cingulum and thalamus differed by pulse pressure level regardless of antihypertensive treatment. Increased pulse pressure may lead to widespread injury to white matter and subcortical structures, with greatest vulnerability for women in late middle to early older age. Restriction spectrum imaging could be useful for monitoring microstructural changes indicative of neuronal loss or shrinkage, demyelination, or inflammation that accompany age-related cerebrovascular dysfunction.

Objective: Abnormal white matter (AWM) on magnetic resonance imaging is associated with cognitive performance in older adults. We explored cognitive associations with AWM during late-midlife. Method: Participants were community-dwelling men (n = 242; M = 61.90 years; range = 56-66). Linear-mixed effects regression models examined associations of total, periventricular, and deep AWM with cognitive performance, controlling for multiple comparisons. Models considering specific cognitive domains controlled for current general cognitive ability (GCA). We hypothesized that total AWM would be associated with worse processing speed, executive function, and current GCA; deep AWM would correlate with GCA and periventricular AWM would relate to specific cognitive abilities. We also assessed the potential influence of cognitive reserve by examining a moderation effect of early life (mean age of 20) cognition. Results: Greater total and deep AWM were associated with poorer current GCA. Periventricular AWM was associated with worse executive function, working memory, and episodic memory. When periventricular and deep AWM were modeled simultaneously, both retained their respective significant associations with cognitive performance. Cognitive reserve did not moderate associations. Conclusions: Our findings suggest that AWM contributes to poorer cognitive function in late-midlife. Examining only total AWM may obscure the potential differential impact of regional AWM. Separating total AWM into subtypes while controlling for current GCA revealed a dissociation in relationships with cognitive performance; deep AWM was associated with nonspecific cognitive ability whereas periventricular AWM was associated with specific frontal-related abilities and memory. Management of vascular or other risk factors that may increase the risk of AWM should begin during or before early late-midlife. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Normal brain aging is characterized by declining neuronal integrity, yet it remains unclear how microstructural injury influences cognitive aging and whether such mechanisms differ between sexes. Using restriction spectrum imaging (RSI), we examined sex differences in associations between brain microstructure and cognitive function in 147 community-dwelling older men and women (56-99 years). Gray and white matter microstructure correlated with global cognition, executive function, visuospatial memory, episodic memory, and logical memory, with the strongest associations for restricted, hindered and free isotropic diffusion. Associations were stronger for women than for men, a difference likely due to greater age-related variability in cognitive scores and microstructure in women. Isotropic diffusion mediated effects of age on cognition for both sexes, though distinct mediation patterns were present for women and men. For women, hippocampal and corpus callosum microstructure mediated age effects on verbal and visuospatial memory, respectively, whereas for men fiber microstructure (mainly fornix and corpus callosum) mediated age effects on executive function and visuospatial memory. These findings implicate sex-specific pathways by which changing brain cytoarchitecture contributes to cognitive aging, and suggest that RSI may be useful for evaluating risk for cognitive decline or monitoring efficacy of interventions to preserve brain health in later life.

Cytoarchitectural brain changes during normal aging remain poorly characterized, and it is unclear whether patterns of brain aging differ by sex. This study used restriction spectrum imaging to examine associations between age and brain microstructure in 147 community-dwelling participants (aged 56-99 years). Widespread associations with age in multiple diffusion compartments, including increased free water, decreased restricted and hindered diffusion, and reduced neurite complexity, were observed in the cortical gray matter, the white matter tracts, and the hippocampus. Age differences in cortical microstructure were largely independent of atrophy. Associations were mostly global, although foci of stronger effects emerged in the fornix, anterior thalamic radiation and commissural fibers, and the medial temporal, orbitofrontal, and occipital cortices. Age differences were stronger and more widespread for women than men, even after adjustment for education, hypertension, and body mass index. Restriction spectrum imaging may be a convenient, noninvasive tool for monitoring changes in diffusion properties that are thought to reflect reduced cellular fractions and neurite density or complexity, which occur with typical aging, and for detecting sex differences in patterns of brain aging.

The prevalence of obesity in children and adolescents worldwide has quadrupled since 1975 and is a key predictor of obesity later in life. Previous work has consistently observed relationships between macroscale measures of reward-related brain regions (e.g., the nucleus accumbens [NAcc]) and unhealthy eating behaviors and outcomes; however, the mechanisms underlying these associations remain unclear. Recent work has highlighted a potential role of neuroinflammation in the NAcc in animal models of diet-induced obesity. Here, we leverage a diffusion MRI technique, restriction spectrum imaging, to probe the microstructure (cellular density) of subcortical brain regions. More specifically, we test the hypothesis that the cell density of reward-related regions is associated with obesity-related metrics and early weight gain. In a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain Cognitive Development (ABCD) study, we demonstrate that cellular density in the NAcc is related to individual differences in waist circumference at baseline and is predictive of increases in waist circumference after 1 y. These findings suggest a neurobiological mechanism for pediatric obesity consistent with rodent work showing that high saturated fat diets increase gliosis and neuroinflammation in reward-related brain regions, which in turn lead to further unhealthy eating and obesity.

Working memory function changes across development and varies across individuals. The patterns of behavior and brain function that track individual differences in working memory during human development, however, are not well understood. Here, we establish associations between working memory, other cognitive abilities, and functional MRI (fMRI) activation in data from over 11,500 9- to 10-year-old children (both sexes) enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Analyses relating out-of-scanner working memory performance to memory-related fMRI activation in an emotional n-back task demonstrate that frontoparietal activity during a working memory challenge indexes working memory performance. This relationship is domain specific, such that fMRI activation related to emotion processing during the emotional n-back task, inhibitory control during a stop-signal task (SST), and reward processing during a monetary incentive delay (MID) task does not track memory abilities. Together, these results inform our understanding of individual differences in working memory in childhood and lay the groundwork for characterizing the ways in which they change across adolescence.SIGNIFICANCE STATEMENT Working memory is a foundational cognitive ability that changes over time and varies across individuals. Here, we analyze data from over 11,500 9- to 10-year-olds to establish relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges. Our results lay the groundwork for assessing longitudinal changes in working memory and predicting later academic and other real-world outcomes.

Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.

BackgroundAlthough amyloid-β (Aβ) and microstructural brain changes are both effective biomarkers of Alzheimer's disease, their independent or synergistic effects on cognitive decline are unclear.ObjectiveTo examine associations of Aβ and brain microstructure with cognitive decline in amnestic mild cognitive impairment and dementia.MethodsRestriction spectrum imaging, cerebrospinal fluid Aβ, and longitudinal cognitive data were collected on 23 healthy controls and 13 individuals with mild cognitive impairment or mild to moderate Alzheimer's disease. Neurite density (ND) and isotropic free water diffusion (IF) were computed in fiber tracts and cortical regions of interest. We examined associations of Aβ with regional and whole-brain microstructure, and assessed whether microstructure mediates effects of Aβ on cognitive decline.ResultsLower ND in limbic and association fibers and higher medial temporal lobe IF predicted baseline impairment and longitudinal decline across multiple cognitive domains. ND and IF predicted cognitive outcomes after adjustment for Aβ or whole-brain microstructure. Correlations between microstructure and cognition were present for both amyloid-positive and amyloid-negative individuals. Aβ correlated with whole-brain, rather than regional, ND and IF.ConclusionAβ correlates with widespread microstructural brain changes, whereas regional microstructure correlates with cognitive decline. Microstructural abnormalities predict cognitive decline regardless of amyloid, and may inform about neural injury leading to cognitive decline beyond that attributable to amyloid.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

ObjectivesTemporal lobe epilepsy (TLE) is known to affect large-scale gray and white matter networks, and these network changes likely contribute to the verbal memory impairments observed in many patients. In this study, we investigate multimodal imaging patterns of brain alterations in TLE and evaluate the sensitivity of different imaging measures to verbal memory impairment.MethodsDiffusion tensor imaging (DTI), volumetric magnetic resonance imaging (vMRI), and resting-state functional MRI (rs-fMRI) were evaluated in 46 patients with TLE and 33 healthy controls to measure patterns of microstructural, structural, and functional alterations, respectively. These measurements were obtained within the white matter directly beneath neocortex (ie, superficial white matter [SWM]) for DTI and across neocortex for vMRI and rs-fMRI. The degree to which imaging alterations within left medial temporal lobe/posterior cingulate (LMT/PC) and left lateral temporal regions were associated with verbal memory performance was evaluated.ResultsPatients with left TLE and right TLE both demonstrated pronounced microstructural alterations (ie, decreased fractional anisotropy [FA] and increased mean diffusivity [MD]) spanning the entire frontal and temporolimbic SWM, which were highly lateralized to the ipsilateral hemisphere. Conversely, reductions in cortical thickness in vMRI and alterations in the magnitude of the rs-fMRI response were less pronounced and less lateralized than the microstructural changes. Both stepwise regression and mediation analyses further revealed that FA and MD within SWM in LMT/PC regions were the most robust predictors of verbal memory, and that these associations were independent of left hippocampal volume.SignificanceThese findings suggest that microstructural loss within the SWM is pronounced in patients with TLE, and injury to the SWM within the LMT/PC region plays a critical role in verbal memory impairment.

The human hippocampus can be subdivided into subfields with unique functional properties and differential vulnerability to disease or neuropsychiatric conditions. Identifying genes that confer susceptibility to such processes is an important goal in developing treatments. Recent advances in automatic subfield segmentation from magnetic resonance images make it possible to use these measures as phenotypes in large-scale genome-wide association studies. Such analyses are likely to rely largely on standard resolution (~1 mm isotropic) T1 -weighted images acquired on 3.0T scanners. Determining whether the genetic architecture of subfields can be detected from such images is therefore an important step. We used Freesurfer v6.0 to segment hippocampal subfields in two large twin studies, the Vietnam Era Twin Study of Aging and the Human Connectome Project. We estimated heritability of subfields and the genetic overlap with total hippocampal volume. Heritability was similar across samples, but little genetic variance remained after accounting for genetic influences on total hippocampal volume. Importantly, we examined genetic relationships between subfields to determine whether subfields can be grouped based on a smaller number of underlying, genetically independent factors. We identified three genetic factors in both samples, but the high degree of cross loadings precluded formation of genetically distinct groupings of subfields. These results confirm the reliability of Freesurfer v6.0 generated subfields across samples for phenotypic analyses. However, the current results suggest that it will be difficult for large-scale genetic analyses to identify subfield-specific genes that are distinct from both total hippocampal volume and other subfields using segmentations generated from standard resolution T1 -weighted images.