Longitudinal Association of Amyloid Beta and Anxious-Depressive Symptoms in Cognitively Normal Older Adults.

To understand the role of depressive symptoms in preclinical Alzheimer's disease, it is essential to define their temporal relationship to Alzheimer's proteinopathies in cognitively normal older adults. The study objective was to examine associations of brain amyloid beta and longitudinal measures of depression and depressive symptom clusters in a cognitively normal sample of older adults. A total of 270 community-dwelling, cognitively normal elderly individuals underwent baseline Pittsburgh compound B (PiB) positron emission tomography (PET) measures of cortical aggregate amyloid beta and annual assessments with the 30-item Geriatric Depression Scale (GDS). The authors evaluated continuous PiB binding as a predictor of GDS score or GDS cluster, calculated as total scores and mean scores for three GDS item clusters (apathy-anhedonia, dysphoria, and anxiety-concentration), across time (1-5 years; mean=3.8 years) in separate mixed-effects models with backward elimination. Initial predictors included PiB binding, age, sex, Hollingshead score, American National Adult Reading Test (AMNART) score, apolipoprotein E ε4 status, depression history, and their interactions with time. Higher PiB binding predicted accelerated rates of increase in GDS score over time, adjusting for depression history. Higher PiB binding also predicted steeper rates of increase for anxiety-concentration scores, adjusting for depression history and the AMNART score-by-time interaction. In a post hoc model estimating anxiety scores without concentration disturbance items, the PiB binding-by-time interaction remained significant. Higher amyloid beta burden was associated with increasing anxious-depressive symptoms over time in cognitively normal older individuals. Prior depression history was related to higher but not worsening symptom ratings. These results suggest a direct or indirect association of elevated amyloid beta levels with worsening anxious-depressive symptoms and support the hypothesis that emerging neuropsychiatric symptoms represent an early manifestation of preclinical Alzheimer's disease

PET staging of amyloidosis using striatum.

INTRODUCTION: Amyloid positron emission tomography (PET) data are commonly expressed as binary measures of cortical deposition. However, not all individuals with high cortical amyloid will experience rapid cognitive decline. Motivated by postmortem data, we evaluated a three-stage PET classification: low cortical; high cortical, low striatal; and high cortical, high striatal amyloid; hypothesizing this model could better reflect Alzheimer's dementia progression than a model based only on cortical measures. METHODS: We classified PET data from 1433 participants (646 normal, 574 mild cognitive impairment, and 213 AD), explored the successive involvement of cortex and striatum using 3-year follow-up PET data, and evaluated the associations between PET stages, hippocampal volumes, and cognition. RESULTS: Follow-up data indicated that PET detects amyloid first in cortex and then in striatum. Our three-category staging including striatum better predicted hippocampal volumes and subsequent cognition than a three-category staging including only cortical amyloid. DISCUSSION: PET can evaluate amyloid expansion from cortex to subcortex. Using striatal signal as a marker of advanced amyloidosis may increase predictive power in Alzheimer's dementia research

Defining the Lowest Threshold for Amyloid-PET to Predict Future Cognitive Decline and Amyloid Accumulation.

As clinical trials move toward earlier intervention, we sought to redefine the β-amyloid (Aβ)-PET threshold based on the lowest point in a baseline distribution that robustly predicts future Aβ accumulation and cognitive decline in 3 independent samples of clinically normal individuals. Sequential Aβ cutoffs were tested to identify the lowest cutoff associated with future change in cognition (Preclinical Alzheimer Cognitive Composite [PACC]) and Aβ-PET in clinically normal participants from the Harvard Aging Brain Study (n = 342), Australian Imaging, Biomarker and Lifestyle study of aging (n = 157), and Alzheimer's Disease Neuroimaging Initiative (n = 356). Within samples, cutoffs derived from future Aβ-PET accumulation and PACC decline converged on the same inflection point, beyond which trajectories diverged from normal. Across samples, optimal cutoffs fell within a short range (Centiloid 15-18.5). These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. Threshold convergence raises the possibility of contemporaneous early changes in Aβ and cognition. This study provides Class II evidence that among clinically normal individuals a specific Aβ-PET threshold is predictive of cognitive decline

PET staging of amyloidosis using striatum

Amyloid PET data are commonly expressed as binary measures of cortical deposition. However, not all individuals with high cortical amyloid will experience rapid cognitive decline. Motivated by postmortem data, we evaluated a three-stage PET classification: low cortical; high cortical, low striatal; and high cortical, high striatal amyloid; hypothesizing this model could better reflect Alzheimer's dementia progression than a model based only on cortical measures. We classified PET data from 1433 participants (646 normal, 574 mild cognitive impairment, and 213 AD), explored the successive involvement of cortex and striatum using 3-year follow-up PET data, and evaluated the associations between PET stages, hippocampal volumes, and cognition. Follow-up data indicated that PET detects amyloid first in cortex and then in striatum. Our three-category staging including striatum better predicted hippocampal volumes and subsequent cognition than a three-category staging including only cortical amyloid. PET can evaluate amyloid expansion from cortex to subcortex. Using striatal signal as a marker of advanced amyloidosis may increase predictive power in Alzheimer's dementia research

Sex, amyloid, and APOE ε4 and risk of cognitive decline in preclinical Alzheimer's disease: Findings from three well-characterized cohorts.

Our objective was to investigate the effect of sex on cognitive decline within the context of amyloid β (Aβ) burden and apolipoprotein E genotype. We analyzed sex-specific effects on Aβ-positron emission tomography, apolipoprotein, and rates of change on the Preclinical Alzheimer Cognitive Composite-5 across three cohorts, such as the Alzheimer's Disease Neuroimaging Initiative, Australian Imaging, Biomarker and Lifestyle, and Harvard Aging Brain Study (n = 755; clinical dementia rating = 0; age (standard deviation) = 73.6 (6.5); female = 55%). Mixed-effects models of cognitive change by sex, Aβ-positron emission tomography, and apolipoprotein ε4 were examined with quadratic time effects over a median of 4 years of follow-up. Apolipoprotein ε4 prevalence and Aβ burden did not differ by sex. Sex did not directly influence cognitive decline. Females with higher Aβ exhibited faster decline than males. Post hoc contrasts suggested that females who were Aβ and apolipoprotein ε4 positive declined faster than their male counterparts. Although Aβ did not differ by sex, cognitive decline was greater in females with higher Aβ. Our findings suggest that sex may play a modifying role on risk of Alzheimer's disease-related cognitive decline

Brain charts for the human lifespan

Over the past 25 years, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, there are no reference standards against which to anchor measures of individual differences in brain morphology, in contrast to growth charts for traits such as height and weight. Here, we built an interactive online resource ( www.brainchart.io ) to quantify individual differences in brain structure from any current or future magnetic resonance imaging (MRI) study, against models of expected age-related trends. With the goal of basing these on the largest and most inclusive dataset, we aggregated MRI data spanning 115 days post-conception through 100 postnatal years, totaling 122,123 scans from 100,071 individuals in over 100 studies across 6 continents. When quantified as centile scores relative to the reference models, individual differences show high validity with non-MRI brain growth estimates and high stability across longitudinal assessment. Centile scores helped identify previously unreported brain developmental milestones and demonstrated increased genetic heritability compared to non-centiled MRI phenotypes. Crucially for the study of brain disorders, centile scores provide a standardised and interpretable measure of deviation that reveals new patterns of neuroanatomical differences across neurological and psychiatric disorders emerging during development and ageing. In sum, brain charts for the human lifespan are an essential first step towards robust, standardised quantification of individual variation and for characterizing deviation from age-related trends. Our global collaborative study provides such an anchorpoint for basic neuroimaging research and will facilitate implementation of research-based standards in clinical studies

Publisher Correction: Brain charts for the human lifespan.

In the version of this article initially published, there were errors in the affiliations for K. Im (missing affiliation, Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA), J. Lerch (missing affiliation, Mouse Imaging Centre, Toronto, Ontario, Canada), S. Villeneuve and X. N. Zuo (incorrect affiliation numbers listed), H. Yun (missing affiliation, Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA), and H. J. Zar (extra affiliation shown). In addition, the affiliation numbers for all authors listed in the consortium membership section were incorrect by 1–3 digits. The errors have been corrected in the HTML and PDF versions of the article

Brain charts for the human lifespan

10.1038/s41586-022-04554-yNature6047906525-53

Additional file 28 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 28: Table S18. Sex-participation association of the variants with significant sex-specific lipid results

Additional file 17 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Additional file 17: Table S9. PheWAS UKB-MVP meta-analysis results for each index lipid variant at Bonferroni threshold for multiple testing