Longitudinal modeling of age-dependent latent traits with generalized additive latent and mixed models

We present generalized additive latent and mixed models (GALAMMs) for analysis of clustered data with responses and latent variables depending smoothly on observed variables. A scalable maximum likelihood estimation algorithm is proposed, utilizing the Laplace approximation, sparse matrix computation, and automatic differentiation. Mixed response types, heteroscedasticity, and crossed random effects are naturally incorporated into the framework. The models developed were motivated by applications in cognitive neuroscience, and two case studies are presented. First, we show how GALAMMs can jointly model the complex lifespan trajectories of episodic memory, working memory, and speed/executive function, measured by the California Verbal Learning Test (CVLT), digit span tests, and Stroop tests, respectively. Next, we study the effect of socioeconomic status on brain structure, using data on education and income together with hippocampal volumes estimated by magnetic resonance imaging. By combining semiparametric estimation with latent variable modeling, GALAMMs allow a more realistic representation of how brain and cognition vary across the lifespan, while simultaneously estimating latent traits from measured items. Simulation experiments suggest that model estimates are accurate even with moderate sample sizes

Through Thick and Thin: a Need to Reconcile Contradictory Results on Trajectories in Human Cortical Development

Abstract Understanding how brain development normally proceeds is a premise of understanding neurodevelopmental disorders. This has sparked a wealth of magnetic resonance imaging (MRI) studies. Unfortunately, they are in marked disagreement on how the cerebral cortex matures. While cortical thickness increases for the first 8-9 years of life have repeatedly been reported, others find continuous cortical thinning from early childhood, at least from age 3 or 4 years. We review these inconsistencies, and discuss possible reasons, including the use of different scanners, recording parameters and analysis tools, and possible effects of variables such as head motion. When tested on the same subsample, 2 popular thickness estimation methods (CIVET and FreeSurfer) both yielded a continuous thickness decrease from 3 years. Importantly, MRI-derived measures of cortical development are merely our best current approximations, hence the term "apparent cortical thickness" may be preferable. We recommend strategies for reaching consensus in the field, including multimodal neuroimaging to measure phenomena using different techniques, for example, the use of T 1 /T 2 ratio, and data sharing to allow replication across analysis methods. As neurodevelopmental origins of early-and late-onset disease are increasingly recognized, resolving inconsistencies in brain maturation trajectories is important

Structural Brain Imaging of Long-Term Anabolic-Androgenic Steroid Users and Nonusing Weightlifters

AbstractBackgroundProlonged high-dose anabolic-androgenic steroid (AAS) use has been associated with psychiatric symptoms and cognitive deficits, yet we have almost no knowledge of the long-term consequences of AAS use on the brain. The purpose of this study is to investigate the association between long-term AAS exposure and brain morphometry, including subcortical neuroanatomical volumes and regional cortical thickness.MethodsMale AAS users and weightlifters with no experience with AASs or any other equivalent doping substances underwent structural magnetic resonance imaging scans of the brain. The current paper is based upon high-resolution structural T1-weighted images from 82 current or past AAS users exceeding 1 year of cumulative AAS use and 68 non–AAS-using weightlifters. Images were processed with the FreeSurfer software to compare neuroanatomical volumes and cerebral cortical thickness between the groups.ResultsCompared to non–AAS-using weightlifters, the AAS group had thinner cortex in widespread regions and significantly smaller neuroanatomical volumes, including total gray matter, cerebral cortex, and putamen. Both volumetric and thickness effects remained relatively stable across different AAS subsamples comprising various degrees of exposure to AASs and also when excluding participants with previous and current non-AAS drug abuse. The effects could not be explained by differences in verbal IQ, intracranial volume, anxiety/depression, or attention or behavioral problems.ConclusionsThis large-scale systematic investigation of AAS use on brain structure shows negative correlations between AAS use and brain volume and cortical thickness. Although the findings are correlational, they may serve to raise concern about the long-term consequences of AAS use on structural features of the brain

Inflammation, amyloid, and atrophy in the aging brain: relationships with longitudinal changes in cognition

Amyloid deposition occurs in aging, even in individuals free from cognitive symptoms, and is often interpreted as preclinical Alzheimer's disease (AD) pathophysiology. YKL-40 is a marker of neuroinflammation, being increased in AD, and hypothesized to interact with amyloid-B (AB ) in causing cognitive decline early in the cascade of AD pathophysiology. Whether and how A and YKL-40 affect brain and cognitive changes in cognitively healthy older adults is still unknown. We studied 89 participants (mean age: 73.1 years) with cerebrospinal fluid samples at baseline, and both MRI and cognitive assessments from two time-points separated by two years. We tested how baseline levels of AB 42 and YKL-40 correlated with changes in cortical thickness and cognition. Thickness change correlated with AB 42 only in AB 42+ participants (<600 pg/mL, n = 27) in the left motor and premotor cortices. AB 42 was unrelated to cognitive change. Increased YKL-40 was associated with less preservation of scores on the animal naming test in the total sample (r = -0.28, p = 0.012) and less preservation of a score reflecting global cognitive function for AB 42+ participants (r = -0.58, p = 0.004). Our results suggest a role for inflammation in brain atrophy and cognitive changes in cognitively normal older adults, which partly depended on AB accumulation

The Disconnected Brain and Executive Function Decline in Aging

Abstract Higher order speeded cognitive abilities depend on efficient coordination of activity across the brain, rendering them vulnerable to age reductions in structural and functional brain connectivity. The concept of &quot;disconnected aging&quot; has been invoked, suggesting that degeneration of connections between distant brain regions cause cognitive reductions. However, it has not been shown that changes in cognitive functions over time can be explained by simultaneous changes in brain connectivity. We followed 119 young and middle-aged (23-52 years) and older (63-86 years) adults for 3.3 years with repeated assessments of structural and functional brain connectivity and executive functions. We found unique age-related longitudinal reductions in executive function over and above changes in more basic cognitive processes. Intriguingly, 82.5% of the age-related decline in executive function could be explained by changes in connectivity over time. While both structural and functional connectivity changes were related to longitudinal reductions in executive function, only structural connectivity change could explain the age-specific decline. This suggests that the major part of the age-related reductions in executive function can be attributed to micro-and macrostructural alterations in brain connectivity. Although correlational in nature, we believe the present results constitute evidence for a &quot;disconnected brain&quot; view on cognitive aging

Brain imaging and human nutrition: which measures to use in intervention studies?

The present review describes brain imaging technologies that can be used to assess the effects of nutritional interventions in human subjects. Specifically, we summarise the biological relevance of their outcome measures, practical use and feasibility, and recommended use in short- and long-term nutritional studies. The brain imaging technologies described consist of MRI, including diffusion tensor imaging, magnetic resonance spectroscopy and functional MRI, as well as electroencephalography/magnetoencephalography, near-IR spectroscopy, positron emission tomography and single-photon emission computerised tomography. In nutritional interventions and across the lifespan, brain imaging can detect macro- and microstructural, functional, electrophysiological and metabolic changes linked to broader functional outcomes, such as cognition. Imaging markers can be considered as specific for one or several brain processes and as surrogate instrumental endpoints that may provide sensitive measures of short- and long-term effects. For the majority of imaging measures, little information is available regarding their correlation with functional endpoints in healthy subjects; therefore, imaging markers generally cannot replace clinical endpoints that reflect the overall capacity of the brain to behaviourally respond to specific situations and stimuli. The principal added value of brain imaging measures for human nutritional intervention studies is their ability to provide unique in vivo information on the working mechanism of an intervention in hypothesis-driven research. Selection of brain imaging techniques and target markers within a given technique should mainly depend on the hypothesis regarding the mechanism of action of the intervention, level (structural, metabolic or functional) and anticipated timescale of the intervention's effects, target population, availability and costs of the technique

Longitudinal association between hippocampus atrophy and episodic-memory decline in non-demented APOE ε4 carriers.

Introduction: The apolipoprotein E (APOE) ε4 allele is the main genetic risk factor for Alzheimer's disease (AD), accelerated cognitive aging, and hippocampal atrophy, but its influence on the association between hippocampus atrophy and episodic-memory decline in non-demented individuals remains unclear. Methods: We analyzed longitudinal (two to six observations) magnetic resonance imaging (MRI)-derived hippocampal volumes and episodic memory from 748 individuals (55 to 90 years at baseline, 50% female) from the European Lifebrain consortium. Results: The change-change association for hippocampal volume and memory was significant only in ε4 carriers (N = 173, r = 0.21, P = .007; non-carriers: N = 467, r = 0.073, P = .117). The linear relationship was significantly steeper for the carriers [t(629) = 2.4, P = .013]. A similar trend toward a stronger change-change relation for carriers was seen in a subsample with more than two assessments. Discussion: These findings provide evidence for a difference in hippocampus-memory association between ε4 carriers and non-carriers, thus highlighting how genetic factors modulate the translation of the AD-related pathophysiological cascade into cognitive deficits

Healthy minds 0-100 years: Optimising the use of European brain imaging cohorts ("Lifebrain").

The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.This research is funded by the EU Horizon 2020 Grant: ‘Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”)’. Grant agreement number: 732592. Call: Societal challenges: Health, demographic change and well-bein

People's interest in brain health testing: Findings from an international, online cross-sectional survey

Brain health entails mental wellbeing and cognitive health in the absence of brain disorders. The past decade has seen an explosion of tests, cognitive and biological, to predict various brain conditions, such as Alzheimer's Disease. In line with these current developments, we investigated people's willingness and reasons to—or not to—take a hypothetical brain health test to learn about risk of developing a brain disease, in a cross-sectional multilanguage online survey. The survey was part of the Global Brain Health Survey, open to the public from 4th June 2019 to 31st August 2020. Respondents were largely recruited via European brain councils and research organizations. 27,590 people responded aged 18 years or older and were predominantly women (71%), middle-aged or older (>40 years; 83%), and highly educated (69%). Responses were analyzed to explore the relationship between demographic variables and responses. Results: We found high public interest in brain health testing: over 91% would definitely or probably take a brain health test and 86% would do so even if it gave information about a disease that cannot be treated or prevented. The main reason for taking a test was the ability to respond if one was found to be at risk of brain disease, such as changing lifestyle, seeking counseling or starting treatment. Higher interest in brain health testing was found in men, respondents with lower education levels and those with poor self-reported cognitive health. Conclusion: High public interest in brain health and brain health testing in certain segments of society, coupled with an increase of commercial tests entering the market, is likely to put pressure on public health systems to inform the public about brain health testing in years to come.publishedVersio

Educational attainment does not influence brain aging.

Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging