Functional topography of the neocortex predicts covariation in complex cognitive and basic motor abilities.

Although higher-order cognitive and lower-order sensorimotor abilities are generally regarded as distinct and studied separately, there is evidence that they not only covary but also that this covariation increases across the lifespan. This pattern has been leveraged in clinical settings where a simple assessment of sensory or motor ability (e.g. hearing, gait speed) can forecast age-related cognitive decline and risk for dementia. However, the brain mechanisms underlying cognitive, sensory, and motor covariation are largely unknown. Here, we examined whether such covariation in midlife reflects variability in common versus distinct neocortical networks using individualized maps of functional topography derived from BOLD fMRI data collected in 769 45-year-old members of a population-representative cohort. Analyses revealed that variability in basic motor but not hearing ability reflected individual differences in the functional topography of neocortical networks typically supporting cognitive ability. These patterns suggest that covariation in motor and cognitive abilities in midlife reflects convergence of function in higher-order neocortical networks and that gait speed may not be simply a measure of physical function but rather an integrative index of nervous system health.

Brain morphometry in older adults with and without dementia using extremely rapid structural scans.

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.

Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient.

Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain-wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory-to-association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test-retest data from the young adult Human Connectome Project (HCP-YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge-wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting-state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP-aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP-YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge-wise FC measures in the search for brain-behavior associations.

Brain-age in midlife is associated with accelerated biological aging and cognitive decline in a longitudinal birth cohort.

An individual's brainAGE is the difference between chronological age and age predicted from machine-learning models of brain-imaging data. BrainAGE has been proposed as a biomarker of age-related deterioration of the brain. Having an older brainAGE has been linked to Alzheimer's, dementia, and mortality. However, these findings are largely based on cross-sectional associations which can confuse age differences with cohort differences. To illuminate the validity of brainAGE as a biomarker of accelerated brain aging, a study is needed of a large cohort all born in the same year who nevertheless vary on brainAGE. In the Dunedin Study, a population-representative 1972-73 birth cohort, we measured brainAGE at age 45 years, as well as the pace of biological aging and cognitive decline in longitudinal data from childhood to midlife (N = 869). In this cohort, all chronological age 45 years, brainAGE was measured reliably (ICC = 0.81) and ranged from 24 to 72 years. Those with older midlife brainAGEs tended to have poorer cognitive function in both adulthood and childhood, as well as impaired brain health at age 3. Furthermore, those with older brainAGEs had an accelerated pace of biological aging, older facial appearance, and early signs of cognitive decline from childhood to midlife. These findings help to validate brainAGE as a potential surrogate biomarker for midlife intervention studies that seek to measure dementia-prevention efforts in midlife. However, the findings also caution against the assumption that brainAGE scores represent only age-related deterioration of the brain as they may also index central nervous system variation present since childhood.

What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis.

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.

Williams syndrome hemideletion and LIMK1 variation both affect dorsal stream functional connectivity.

Williams syndrome is a rare genetic disorder caused by hemizygous deletion of ∼1.6 Mb affecting 26 genes on chromosome 7 (7q11.23) and is clinically typified by two cognitive/behavioural hallmarks: marked visuospatial deficits relative to verbal and non-verbal reasoning abilities and hypersocial personality. Clear knowledge of the circumscribed set of genes that are affected in Williams syndrome, along with the well-characterized neurobehavioural phenotype, offers the potential to elucidate neurogenetic principles that may apply in genetically and clinically more complex settings. The intraparietal sulcus, in the dorsal visual processing stream, has been shown to be structurally and functionally altered in Williams syndrome, providing a target for investigating resting-state functional connectivity and effects of specific genes hemideleted in Williams syndrome. Here, we tested for effects of the LIMK1 gene, deleted in Williams syndrome and important for neuronal maturation and migration, on intraparietal sulcus functional connectivity. We first defined a target brain phenotype by comparing intraparietal sulcus resting functional connectivity in individuals with Williams syndrome, in whom LIMK1 is hemideleted, with typically developing children. Then in two separate cohorts from the general population, we asked whether intraparietal sulcus functional connectivity patterns similar to those found in Williams syndrome were associated with sequence variation of the LIMK1 gene. Four independent between-group comparisons of resting-state functional MRI data (total n = 510) were performed: (i) 20 children with Williams syndrome compared to 20 age- and sex-matched typically developing children; (ii) a discovery cohort of 99 healthy adults stratified by LIMK1 haplotype; (iii) a replication cohort of 32 healthy adults also stratified by LIMK1 haplotype; and (iv) 339 healthy adolescent children stratified by LIMK1 haplotype. For between-group analyses, differences in intraparietal sulcus resting-state functional connectivity were calculated comparing children with Williams syndrome to matched typically developing children and comparing LIMK1 haplotype groups in each of the three general population cohorts separately. Consistent with the visuospatial construction impairment and hypersocial personality that typify Williams syndrome, the Williams syndrome cohort exhibited opposite patterns of intraparietal sulcus functional connectivity with visual processing regions and social processing regions: decreased circuit function in the former and increased circuit function in the latter. All three general population groups also showed LIMK1 haplotype-related differences in intraparietal sulcus functional connectivity localized to the fusiform gyrus, a visual processing region also identified in the Williams syndrome-typically developing comparison. These results suggest a neurogenetic mechanism, in part involving LIMK1, that may bias neural circuit function in both the general population and individuals with Williams syndrome.

A Polygenic Score for Higher Educational Attainment is Associated with Larger Brains.

People who score higher on intelligence tests tend to have larger brains. Twin studies suggest the same genetic factors influence both brain size and intelligence. This has led to the hypothesis that genetics influence intelligence partly by contributing to the development of larger brains. We tested this hypothesis using four large imaging genetics studies (combined N = 7965) with polygenic scores derived from a genome-wide association study (GWAS) of educational attainment, a correlate of intelligence. We conducted meta-analysis to test associations among participants' genetics, total brain volume (i.e., brain size), and cognitive test performance. Consistent with previous findings, participants with higher polygenic scores achieved higher scores on cognitive tests, as did participants with larger brains. Participants with higher polygenic scores also had larger brains. We found some evidence that brain size partly mediated associations between participants' education polygenic scores and their cognitive test performance. Effect sizes were larger in the population-based samples than in the convenience-based samples. Recruitment and retention of population-representative samples should be a priority for neuroscience research. Findings suggest promise for studies integrating GWAS discoveries with brain imaging to understand neurobiology linking genetics with cognitive performance.

Association of Childhood Lead Exposure With MRI Measurements of Structural Brain Integrity in Midlife.

Importance: Childhood lead exposure has been linked to disrupted brain development, but long-term consequences for structural brain integrity are unknown. Objective: To test the hypothesis that childhood lead exposure is associated with magnetic resonance imaging (MRI) measurements of lower structural integrity of the brain in midlife. Design, Setting, and Participants: The Dunedin Study followed a population-representative 1972-1973 birth cohort in New Zealand (N = 564 analytic sample) to age 45 years (until April 2019). Exposures: Childhood blood lead levels measured at age 11 years. Main Outcomes and Measures: Structural brain integrity at age 45 years assessed via MRI (primary outcomes): gray matter (cortical thickness, surface area, hippocampal volume), white matter (white matter hyperintensities, fractional anisotropy [theoretical range, 0 {diffusion is perfectly isotropic} to 100 {diffusion is perfectly anisotropic}]), and the Brain Age Gap Estimation (BrainAGE), a composite index of the gap between chronological age and a machine learning algorithm-estimated brain age (0 indicates a brain age equivalent to chronological age; positive and negative values represent an older and younger brain age, respectively). Cognitive function at age 45 years was assessed objectively via the Wechsler Adult Intelligence Scale IV (IQ range, 40-160, standardized to a mean of 100 [SD, 15]) and subjectively via informant and self-reports (z-score units; scale mean, 0 [SD, 1]). Results: Of 1037 original participants, 997 were alive at age 45 years, of whom 564 (57%) had received lead testing at age 11 years (302 [54%] male) (median follow-up, 34 [interquartile range, 33.7-34.7] years). Mean blood lead level at age 11 years was 10.99 (SD, 4.63) µg/dL. After adjusting for covariates, each 5-µg/dL higher childhood blood lead level was significantly associated with 1.19-cm2 smaller cortical surface area (95% CI, -2.35 to -0.02 cm2; P = .05), 0.10-cm3 smaller hippocampal volume (95% CI, -0.17 to -0.03 cm3; P = .006), lower global fractional anisotropy (b = -0.12; 95% CI, -0.24 to -0.01; P = .04), and a BrainAGE index 0.77 years older (95% CI, 0.02-1.51 years; P = .05) at age 45 years. There were no statistically significant associations between blood lead level and log-transformed white matter hyperintensity volume (b = 0.05 log mm3; 95% CI, -0.02 to 0.13 log mm3; P = .17) or mean cortical thickness (b = -0.004 mm; 95% CI, -0.012 to 0.004 mm; P = .39). Each 5-µg/dL higher childhood blood lead level was significantly associated with a 2.07-point lower IQ score at age 45 years (95% CI, -3.39 to -0.74; P = .002) and a 0.12-point higher score on informant-rated cognitive problems (95% CI, 0.01-0.23; P = .03). There was no statistically significant association between childhood blood lead levels and self-reported cognitive problems (b = -0.02 points; 95% CI, -0.10 to 0.07; P = .68). Conclusions and Relevance: In this longitudinal cohort study with a median 34-year follow-up, higher childhood blood lead level was associated with differences in some MRI measures of brain structure that suggested lower structural brain integrity in midlife. Because of the large number of statistical comparisons, some findings may represent type I error.

General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks.

Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.

A genome-wide association study-derived polygenic score for interleukin-1ß is associated with hippocampal volume in two samples.

Accumulating research suggests that the pro-inflammatory cytokine interleukin-1ß (IL-1ß) has a modulatory effect on the hippocampus, a brain structure important for learning and memory as well as linked with both psychiatric and neurodegenerative disorders. Here, we used an imaging genetics strategy to test an association between an IL-1ß polygenic score and hippocampal volume in two independent samples. Our polygenic score was derived using summary statistics from a recent genome-wide association study of circulating cytokines that included IL-1ß (N = 3,309). In the first sample of 512 non-Hispanic Caucasian university students (274 women, mean age 19.78 ± 1.24 years) from the Duke Neurogenetics Study, we identified a significant positive correlation between IL-1ß polygenic scores and hippocampal volume. This positive association was successfully replicated in a second sample of 7,960 white British volunteers (4,158 women, mean age 62.63 ± 7.45 years) from the UK Biobank. Our results lend further support in humans, to the link between IL-1ß and the structure of the hippocampus.

Microstructural integrity of white matter moderates an association between childhood adversity and adult trait anger.

Amongst a number of negative life sequelae associated with childhood adversity is the later expression of a higher dispositional tendency to experience anger and frustration to a wide range of situations (i.e., trait anger). We recently reported that an association between childhood adversity and trait anger is moderated by individual differences in both threat-related amygdala activity and executive control-related dorsolateral prefrontal cortex (dlPFC) activity, wherein individuals with relatively low amygdala and high dlPFC activity do not express higher trait anger even when having experienced childhood adversity. Here, we examine possible structural correlates of this functional dynamic using diffusion magnetic resonance imaging data from 647 young adult men and women volunteers. Specifically, we tested whether the degree of white matter microstructural integrity as indexed by fractional anisotropy modulated the association between childhood adversity and trait anger. Our analyses revealed that higher microstructural integrity of multiple pathways was associated with an attenuated link between childhood adversity and adult trait anger. Amongst these pathways was the uncinate fasciculus (UF; ΔR 2 = 0.01), which not only provides a major anatomical link between the amygdala and prefrontal cortex but also is associated with individual differences in regulating negative emotion through top-down cognitive reappraisal. These findings suggest that higher microstructural integrity of distributed white matter pathways including but not limited to the UF may represent an anatomical foundation serving to buffer against the expression of childhood adversity as later trait anger, which is itself associated with multiple negative health outcomes.

Reward-Related Ventral Striatum Activity Buffers against the Experience of Depressive Symptoms Associated with Sleep Disturbances.

Sleep disturbances represent one risk factor for depression. Reward-related brain function, particularly the activity of the ventral striatum (VS), has been identified as a potential buffer against stress-related depression. We were therefore interested in testing whether reward-related VS activity would moderate the effect of sleep disturbances on depression in a large cohort of young adults. Data were available from 1129 university students (mean age 19.71 ± 1.25 years; 637 women) who completed a reward-related functional MRI task to assay VS activity and provided self-reports of sleep using the Pittsburgh Sleep Quality Index and symptoms of depression using a summation of the General Distress/Depression and Anhedonic Depression subscales of the Mood and Anxiety Symptoms Questionnaire-short form. Analyses revealed that as VS activity increased the association between sleep disturbances and depressive symptoms decreased. The interaction between sleep disturbances and VS activity was robust to the inclusion of sex, age, race/ethnicity, past or present clinical disorder, early and recent life stress, and anxiety symptoms, as well as the interactions between VS activity and early or recent life stress as covariates. We provide initial evidence that high reward-related VS activity may buffer against depressive symptoms associated with poor sleep. Our analyses help advance an emerging literature supporting the importance of individual differences in reward-related brain function as a potential biomarker of relative risk for depression.SIGNIFICANCE STATEMENT Sleep disturbances are a common risk factor for depression. An emerging literature suggests that reward-related activity of the ventral striatum (VS), a brain region critical for motivation and goal-directed behavior, may buffer against the effect of negative experiences on the development of depression. Using data from a large sample of 1129 university students we demonstrate that as reward-related VS activity increases, the link between sleep disturbances and depression decreases. This finding contributes to accumulating research demonstrating that reward-related brain function may be a useful biomarker of relative risk for depression in the context of negative experiences.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts.

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

An estimate of the longitudinal pace of aging from a single brain scan predicts dementia conversion, morbidity, and mortality.

To understand how aging affects functional decline and increases disease risk, it is necessary to develop accurate and reliable measures of how fast a person is aging. Epigenetic clocks measure aging but require DNA methylation data, which many studies lack. Using data from the Dunedin Study, we introduce an accurate and reliable measure for the rate of longitudinal aging derived from cross-sectional brain MRI: the Dunedin Pace of Aging Calculated from NeuroImaging or DunedinPACNI. Exporting this measure to the Alzheimer's Disease Neuroimaging Initiative and UK Biobank neuroimaging datasets revealed that faster DunedinPACNI predicted participants' cognitive impairment, accelerated brain atrophy, and conversion to diagnosed dementia. Underscoring close links between longitudinal aging of the body and brain, faster DunedinPACNI also predicted physical frailty, poor health, future chronic diseases, and mortality in older adults. Furthermore, DunedinPACNI followed the expected socioeconomic health gradient. When compared to brain age gap, an existing MRI aging biomarker, DunedinPACNI was similarly or more strongly related to clinical outcomes. DunedinPACNI is a "next generation" MRI measure that will be made publicly available to the research community to help accelerate aging research and evaluate the effectiveness of dementia prevention and anti-aging strategies.

Precision Brain Morphometry Using Cluster Scanning.

Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.

Functional Topography of the Neocortex Predicts Covariation in Complex Cognitive and Basic Motor Abilities.

Although higher-order cognitive and lower-order sensorimotor abilities are generally regarded as distinct and studied separately, there is evidence that they not only covary but also that this covariation increases across the lifespan. This pattern has been leveraged in clinical settings where a simple assessment of sensory or motor ability (e.g., hearing, gait speed) can forecast age-related cognitive decline and risk for dementia. However, the brain mechanisms underlying cognitive, sensory, and motor covariation are largely unknown. Here, we examined whether such covariation in midlife reflects variability in common versus distinct neocortical networks using individualized maps of functional topography derived from BOLD fMRI data collected in 769 45-year old members of a population-representative cohort. Analyses revealed that variability in basic motor but not hearing ability reflected individual differences in the functional topography of neocortical networks typically supporting cognitive ability. These patterns suggest that covariation in motor and cognitive abilities in midlife reflects convergence of function in higher-order neocortical networks and that gait speed may not be simply a measure of physical function but rather an integrative index of nervous system health.

A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts.

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

A Connectome-wide Functional Signature of Trait Anger.

Past research on the brain correlates of trait anger has been limited by small sample sizes, a focus on relatively few regions-of-interest, and poor test-retest reliability of functional brain measures. To address these limitations, we conducted a data-driven analysis of variability in connectome-wide functional connectivity in a sample of 1,048 young adult volunteers. Multi-dimensional matrix regression analysis showed that self-reported trait anger maps onto variability in the whole-brain functional connectivity patterns of three brain regions that serve action-related functions: bilateral supplementary motor area (SMA) and the right lateral frontal pole. We then demonstrate trait anger modulates the functional connectivity of these regions with canonical brain networks supporting somatomotor, affective, self-referential, and visual information processes. Our findings offer novel neuroimaging evidence for interpreting trait anger as a greater propensity to provoked action, supporting ongoing efforts to understand its utility as a potential transdiagnostic marker for disordered states characterized by aggressive behavior.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia.

BACKGROUND AND OBJECTIVES: DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults. METHODS: We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia. RESULTS: In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]). DISCUSSION: Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.