Compositional structural brain signatures capture Alzheimer's genetic risk on brain structure along the disease continuum.

INTRODUCTION: Traditional brain imaging genetics studies have primarily focused on how genetic factors influence the volume of specific brain regions, often neglecting the overall complexity of brain architecture and its genetic underpinnings. METHODS: This study analyzed data from participants across the Alzheimer's disease (AD) continuum from the ALFA and ADNI studies. We exploited compositional data analysis to examine relative brain volumetric variations that (i) differentiate cognitively unimpaired (CU) individuals, defined as amyloid-negative (A-) based on CSF profiling, from those at different AD stages, and (ii) associated with increased genetic susceptibility to AD, assessed using polygenic risk scores. RESULTS: Distinct brain signatures differentiated CU A-individuals from amyloid-positive MCI and AD. Moreover, disease stage-specific signatures were associated with higher genetic risk of AD. DISCUSSION: The findings underscore the complex interplay between genetics and disease stages in shaping brain structure, which could inform targeted preventive strategies and interventions in preclinical AD.

Early Unguided Human Brain Organoid Neurovascular Niche Modeling into the Permissive Chick Embryo Chorioallantoic Membrane.

Engrafting organoids into vascularized tissues in model animals, such as the immunodeficient mouse or chick embryo chorioallantoic membrane (CAM), has proven efficient for neovascularization modeling. The CAM is a richly vascularized extraembryonic membrane, which shows limited immunoreactivity, thus becoming an excellent hosting model for human origin cell transplants. This paper describes the strategy to engraft human brain organoids differentiated at multiple maturation stages into the CAM. The cellular composition of brain organoids changes with time, reflecting the milestones of human brain development. We grafted brain organoids at relevant maturation stages: neuroepithelial expansion (18 DIV), early neurogenesis (60 DIV), and early gliogenesis (180 DIV) into the CAM of embryonic day (E)7 chicken embryos. Engrafted brain organoids were harvested 5 days later and their histological features were analyzed. No histological signs of neovascularization in the grafted organoids or abnormal blood vessels adjacent to the graftings were detected. Moreover, remarkable changes were observed in the cellular composition of the grafted organoids, namely, an increase in the number of glial fibrillary acidic protein-positive-reactive astrocytes. However, the cytoarchitectural changes were dependent on the organoid maturation stage. Altogether, these results suggest that brain organoids can grow in the CAM, and they show differences in the cytoarchitecture depending on their maturation stage at grafting.

Atypical cortical hierarchy in Aß-positive older adults and its reflection in spontaneous speech.

Abnormal deposition of Aß amyloid is an early neuropathological marker of Alzheimer's disease (AD), arising long ahead of clinical symptoms. Non-invasive measures of associated early neurofunctional changes, together with easily accessible behavioral readouts of these changes, could be of great clinical benefit. We pursued this aim by investigating large-scale cortical gradients of functional connectivity with functional MRI, which capture the hierarchical integration of cortical functions, together with acoustic-prosodic features from spontaneous speech, in cognitively unimpaired older adults with and without Aß positivity (total N = 188). We predicted distortions of the cortical hierarchy associated with prosodic changes in the Aß + group. Results confirmed substantially altered cortical hierarchies and less variability in these in the Aß + group, together with an increase in quantitative prosodic measures, which correlated with gradient variability as well as digit span test scores. Overall, these findings confirm that long before the clinical stage and objective cognitive impairment, increased risk of cognitive decline as indexed by Aß accumulation is marked by neurofunctional changes in the cortical hierarchy, which are related to automatically extractable speech patterns and alterations in working memory functions.

Genetic characterization of the ALFA study: Uncovering genetic profiles in the Alzheimer's continuum.

INTRODUCTION: In 2013, the ALzheimer's and FAmilies (ALFA) project was established to investigate pathophysiological changes in preclinical Alzheimer's disease (AD), and to foster research on early detection and preventive interventions. METHODS: We conducted a comprehensive genetic characterization of ALFA participants with respect to neurodegenerative/cerebrovascular diseases, AD biomarkers, brain endophenotypes, risk factors and aging biomarkers. We placed particular emphasis on amyloid/tau status and assessed gender differences. Multiple polygenic risk scores were computed to capture different aspects of genetic predisposition. We additionally compared AD risk in ALFA to that across the full disease spectrum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: Results show that the ALFA project has been successful at establishing a cohort of cognitively unimpaired individuals at high genetic predisposition of AD. DISCUSSION: It is, therefore, well-suited to study early pathophysiological changes in the preclinical AD continuum. Highlights Prevalence of ε4 carriers in ALzheimer and FAmilies (ALFA) is higher than in the general European population The ALFA study is highly enriched in Alzheimer's disease (AD) genetic risk factors beyond APOE AD genetic profiles in ALFA are similar to clinical groups along the continuum ALFA has succeeded in establishing a cohort of cognitively unimpaired individuals at high genetic AD risk ALFA is well suited to study pathogenic events/early pathophysiological changes in AD.

CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions.

MOTIVATION: Coincidence of Convergent Amino Acid Substitutions (CAAS) with phenotypic convergences allow pinpointing genes and even individual mutations that are likely to be associated with trait variation within their phylogenetic context. Such findings can provide useful insights into the genetic architecture of complex phenotypes. RESULTS: Here we introduce CAAStools, a set of bioinformatics tools to identify and validate CAAS in orthologous protein alignments for predefined groups of species representing the phenotypic values targeted by the user. AVAILABILITY AND IMPLEMENTATION: CAAStools source code is available at http://github.com/linudz/caastools, along with documentation and examples.

Understanding the neurological implications of acute and long COVID using brain organoids.

As early as in the acute phase of the coronavirus disease 2019 (COVID-19) pandemic, the research community voiced concerns about the long-term implications of infection. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), like many other viruses, can trigger chronic disorders that last months or even years. Long COVID, the chronic and persistent disorder lasting more than 12 weeks after the primary infection with SARS-CoV-2, involves a variable number of neurological manifestations, ranging from mild to severe and even fatal. In vitro and in vivo modeling suggest that SARS-CoV-2 infection drives changes within neurons, glia and the brain vasculature. In this Review, we summarize the current understanding of the neuropathology of acute and long COVID, with particular emphasis on the knowledge derived from brain organoid models. We highlight the advantages and main limitations of brain organoids, leveraging their human-derived origin, their similarity in cellular and tissue architecture to human tissues, and their potential to decipher the pathophysiology of long COVID.

Polygenic risk scores enhance prediction of body mass index increase in individuals with a first episode of psychosis.

BACKGROUND: Individuals with a first episode of psychosis (FEP) show rapid weight gain during the first months of treatment, which is associated with a reduction in general physical health. Although genetics is assumed to be a significant contributor to weight gain, its exact role is unknown. METHODS: We assembled a population-based FEP cohort of 381 individuals that was split into a Training (n = 224) set and a Validation (n = 157) set to calculate the polygenic risk score (PRS) in a two-step process. In parallel, we obtained reference genome-wide association studies for body mass index (BMI) and schizophrenia (SCZ) to examine the pleiotropic landscape between the two traits. BMI PRSs were added to linear models that included sociodemographic and clinical variables to predict BMI increase (∆BMI) in the Validation set. RESULTS: The results confirmed considerable shared genetic susceptibility for the two traits involving 449 near-independent genomic loci. The inclusion of BMI PRSs significantly improved the prediction of ∆BMI at 12 months after the onset of antipsychotic treatment by 49.4% compared to a clinical model. In addition, we demonstrated that the PRS containing pleiotropic information between BMI and SCZ predicted ∆BMI better at 3 (12.2%) and 12 months (53.2%). CONCLUSIONS: We prove for the first time that genetic factors play a key role in determining ∆BMI during the FEP. This finding has important clinical implications for the early identification of individuals most vulnerable to weight gain and highlights the importance of examining genetic pleiotropy in the context of medically important comorbidities for predicting future outcomes.

Genetically predicted telomere length and Alzheimer's disease endophenotypes: a Mendelian randomization study.

Telomere length (TL) is associated with biological aging, consequently influencing the risk of age-related diseases such as Alzheimer's disease (AD). We aimed to evaluate the potential causal role of TL in AD endophenotypes (i.e., cognitive performance, N = 2233; brain age and AD-related signatures, N = 1134; and cerebrospinal fluid biomarkers (CSF) of AD and neurodegeneration, N = 304) through a Mendelian randomization (MR) analysis. Our analysis was conducted in the context of the ALFA (ALzheimer and FAmilies) study, a population of cognitively healthy individuals at risk of AD. A total of 20 single nucleotide polymorphisms associated with TL were used to determine the effect of TL on AD endophenotypes. Analyses were adjusted by age, sex, and years of education. Stratified analyses by APOE-ɛ4 status and polygenic risk score of AD were conducted. MR analysis revealed significant associations between genetically predicted longer TL and lower levels of CSF Aß and higher levels of CSF NfL only in APOE-ɛ4 non-carriers. Moreover, inheriting longer TL was associated with greater cortical thickness in age and AD-related brain signatures and lower levels of CSF p-tau among individuals at a high genetic predisposition to AD. Further observational analyses are warranted to better understand these associations.

Genetically predicted telomere length and its relationship with neurodegenerative diseases and life expectancy.

Telomere length (TL) is a biomarker of biological aging. Shorter telomeres have been associated with mortality and increased rates of age-related diseases. However, observational studies are unable to conclude whether TL is causally associated with those outcomes. Mendelian randomization (MR) was developed for assessing causality using genetic variants in epidemiological research. The objective of this study was to test the potential causal role of TL in neurodegenerative disorders and life expectancy through MR analysis. Summary level data were extracted from the most recent genome-wide association studies for TL, Alzheimer's disease (AD), Parkinson's disease, Frontotemporal dementia, Amyotrophic Lateral Sclerosis, Progressive Supranuclear Palsy and life expectancy. MR estimates revealed that longer telomeres inferred a protective effect on risk of AD (OR = 0.964; adjusted p-value = 0.039). Moreover, longer telomeres were significantly associated with increased life expectancy (ßIVW  = 0.011; adjusted p-value = 0.039). Sensitivity analyses suggested evidence for directional pleiotropy in AD analyses. Our results showed that genetically predicted longer TL may increase life expectancy and play a protective causal effect on AD. We did not observe significant causal relationships between longer TL and other neurodegenerative diseases. This suggests that the involvement of TL on specific biological mechanisms might differ between AD and life expectancy, with respect to that in other neurodegenerative diseases. Moreover, the presence of pleiotropy may reflect the complex interplay between TL homeostasis and AD pathophysiology. Further observational studies are needed to confirm these results.

Brain transcriptomic profiling reveals common alterations across neurodegenerative and psychiatric disorders.

Neurodegenerative and neuropsychiatric disorders (ND-NPs) are multifactorial, polygenic and complex behavioral phenotypes caused by brain abnormalities. Large-scale collaborative efforts have tried to identify the genetic architecture of these conditions. However, the specific and shared underlying molecular pathobiology of brain illnesses is not clear. Here, we examine transcriptome-wide characterization of eight conditions, using a total of 2,633 post-mortem brain samples from patients with Alzheimer's disease (AD), Parkinson's disease (PD), Progressive Supranuclear Palsy (PSP), Pathological Aging (PA), Autism Spectrum Disorder (ASD), Schizophrenia (Scz), Major Depressive Disorder (MDD), and Bipolar Disorder (BP)-in comparison with 2,078 brain samples from matched control subjects. Similar transcriptome alterations were observed between NDs and NPs with the top correlations obtained between Scz-BP, ASD-PD, AD-PD, and Scz-ASD. Region-specific comparisons also revealed shared transcriptome alterations in frontal and temporal lobes across NPs and NDs. Co-expression network analysis identified coordinated dysregulations of cell-type-specific modules across NDs and NPs. This study provides a transcriptomic framework to understand the molecular alterations of NPs and NDs through their shared- and specific gene expression in the brain.

Look-alike humans identified by facial recognition algorithms show genetic similarities.

The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of "look-alike" humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide insights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics.

Prepandemic Alzheimer Disease Biomarkers and Anxious-Depressive Symptoms During the COVID-19 Confinement in Cognitively Unimpaired Adults.

BACKGROUND AND OBJECTIVES: Increased anxious-depressive symptomatology is observed in the preclinical stage of Alzheimer disease (AD), which may accelerate disease progression. We investigated whether ß-amyloid, cortical thickness in medial temporal lobe structures, neuroinflammation, and sociodemographic factors were associated with greater anxious-depressive symptoms during the COVID-19 confinement. METHODS: This retrospective observational study included cognitively unimpaired older adults from the Alzheimer's and Families cohort, the majority with a family history of sporadic AD. Participants performed the Hospital Anxiety and Depression Scale (HADS) during the COVID-19 confinement. A subset had available retrospective (on average: 2.4 years before) HADS assessment, amyloid [18F] flutemetamol PET and structural MRI scans, and CSF markers of neuroinflammation (interleukin-6 [IL-6], triggering receptor expressed on myeloid cells 2, and glial fibrillary acidic protein levels). We performed multivariable linear regression models to investigate the associations of prepandemic AD-related biomarkers and sociodemographic factors with HADS scores during the confinement. We further performed an analysis of covariance to adjust by participants' prepandemic anxiety-depression levels. Finally, we explored the role of stress and lifestyle changes (sleep patterns, eating, drinking, smoking habits, and medication use) on the tested associations and performed sex-stratified analyses. RESULTS: We included 921 (254 with AD biomarkers) participants. ß-amyloid positivity (B = 3.73; 95% CI = 1.1 to 6.36; p = 0.006), caregiving (B = 1.37; 95% CI 0.24-2.5; p = 0.018), sex (women: B = 1.95; 95% CI 1.1-2.79; p < 0.001), younger age (B = -0.12; 95% CI -0.18 to -0.052; p < 0.001), and lower education (B = -0.16; 95% CI -0.28 to -0.042; p = 0.008) were associated with greater anxious-depressive symptoms during the confinement. Considering prepandemic anxiety-depression levels, we further observed an association between lower levels of CSF IL-6 (B = -5.11; 95% CI -10.1 to -0.13; p = 0.044) and greater HADS scores. The results were independent of stress-related variables and lifestyle changes. Stratified analysis revealed that the associations were mainly driven by women. DISCUSSION: Our results link AD-related pathophysiology and neuroinflammation with greater anxious-depressive symptomatology during the COVID-19-related confinement, notably in women. AD pathophysiology may increase neuropsychiatric symptomatology in response to stressors. This association may imply a worse clinical prognosis in people at risk for AD after the pandemic and thus deserves to be considered by clinicians. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier NCT02485730.

A quality control portal for sequencing data deposited at the European genome-phenome archive.

Since its launch in 2008, the European Genome-Phenome Archive (EGA) has been leading the archiving and distribution of human identifiable genomic data. In this regard, one of the community concerns is the potential usability of the stored data, as of now, data submitters are not mandated to perform any quality control (QC) before uploading their data and associated metadata information. Here, we present a new File QC Portal developed at EGA, along with QC reports performed and created for 1 694 442 files [Fastq, sequence alignment map (SAM)/binary alignment map (BAM)/CRAM and variant call format (VCF)] submitted at EGA. QC reports allow anonymous EGA users to view summary-level information regarding the files within a specific dataset, such as quality of reads, alignment quality, number and type of variants and other features. Researchers benefit from being able to assess the quality of data prior to the data access decision and thereby, increasing the reusability of data (https://ega-archive.org/blog/data-upcycling-powered-by-ega/).

Human herpesvirus diversity is altered in HLA class I binding peptides.

Herpesviruses are ubiquitous, genetically diverse DNA viruses, with long-term presence in humans associated with infrequent but significant pathology. Human leukocyte antigen (HLA) class I presents intracellularly derived peptide fragments from infected tissue cells to CD8+ T and natural killer cells, thereby directing antiviral immunity. Allotypes of highly polymorphic HLA class I are distinguished by their peptide binding repertoires. Because this HLA class I variation is a major determinant of herpesvirus disease, we examined if sequence diversity of virus proteins reflects evasion of HLA presentation. Using population genomic data from Epstein­Barr virus (EBV), human cytomegalovirus (HCMV), and Varicella­Zoster virus, we tested whether diversity differed between the regions of herpesvirus proteins that can be recognized, or not, by HLA class I. Herpesviruses exhibit lytic and latent infection stages, with the latter better enabling immune evasion. Whereas HLA binding peptides of lytic proteins are conserved, we found that EBV and HCMV proteins expressed during latency have increased peptide sequence diversity. Similarly, latent, but not lytic, herpesvirus proteins have greater population structure in HLA binding than nonbinding peptides. Finally, we found patterns consistent with EBV adaption to the local HLA environment, with less efficient recognition of EBV isolates by high-frequency HLA class I allotypes. Here, the frequency of CD8+ T cell epitopes inversely correlated with the frequency of HLA class I recognition. Previous analyses have shown that pathogen-mediated natural selection maintains exceptional polymorphism in HLA residues that determine peptide recognition. Here, we show that HLA class I peptide recognition impacts diversity of globally widespread pathogens.

Beacon v2 and Beacon networks: A "lingua franca" for federated data discovery in biomedical genomics, and beyond.

Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations. Particularly, rare disease genetics and cancer research will benefit from new case level and genomic variant level requests and the enabling of richer phenotype and clinical queries as well as support for fuzzy searches. Beacon is designed as a "lingua franca" to bridge data collections hosted in software solutions with different and rich interfaces. Beacon version 2 works alongside popular standards like Phenopackets, OMOP, or FHIR, allowing implementing consortia to return matches in beacon responses and provide a handover to their preferred data exchange format. The protocol is being explored by other research domains and is being tested in several international projects.

The European Genome-phenome Archive in 2021.

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles. Launched in 2008, the EGA has grown quickly, currently archiving over 4,500 studies from nearly one thousand institutions. The EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA, therefore, the submitter keeps control on who has access to the data and under which conditions. Given the size and value of data hosted, the EGA is constantly improving its value chain, that is, how the EGA can contribute to enhancing the value of human health data by facilitating its submission, discovery, access, and distribution, as well as leading the design and implementation of standards and methods necessary to deliver the value chain. The EGA has become a key GA4GH Driver Project, leading multiple development efforts and implementing new standards and tools, and has been appointed as an ELIXIR Core Data Resource.

Single-cell Transcriptional Changes in Neurodegenerative Diseases.

In recent decades, our understanding of the molecular changes involved in neurodegenerative diseases has been transformed. Single-cell RNA sequencing and single-nucleus RNA sequencing technologies have been applied to provide cellular and molecular details of the brain at the single-cell level. This has expanded our knowledge of the central nervous system and provided insights into the molecular vulnerability of brain cell types and underlying mechanisms in neurodegenerative diseases. In this review, we highlight the recent advances and findings related to neurodegenerative diseases using these cutting-edge technologies.

Correction: Telford et al. Expanding the Geographic Characterisation of Epstein-Barr Virus Variation through Gene-Based Approaches. Microorganisms 2020, 8, 1686.

The authors wish to make the following correction to this paper [...].

The genetic impact of an Ebola outbreak on a wild gorilla population.

BACKGROUND: Numerous Ebola virus outbreaks have occurred in Equatorial Africa over the past decades. Besides human fatalities, gorillas and chimpanzees have also succumbed to the fatal virus. The 2004 outbreak at the Odzala-Kokoua National Park (Republic of Congo) alone caused a severe decline in the resident western lowland gorilla (Gorilla gorilla gorilla) population, with a 95% mortality rate. Here, we explore the immediate genetic impact of the Ebola outbreak in the western lowland gorilla population. RESULTS: Associations with survivorship were evaluated by utilizing DNA obtained from fecal samples from 16 gorilla individuals declared missing after the outbreak (non-survivors) and 15 individuals observed before and after the epidemic (survivors). We used a target enrichment approach to capture the sequences of 123 genes previously associated with immunology and Ebola virus resistance and additionally analyzed the gut microbiome which could influence the survival after an infection. Our results indicate no changes in the population genetic diversity before and after the Ebola outbreak, and no significant differences in microbial community composition between survivors and non-survivors. However, and despite the low power for an association analysis, we do detect six nominally significant missense mutations in four genes that might be candidate variants associated with an increased chance of survival. CONCLUSION: This study offers the first insight to the genetics of a wild great ape population before and after an Ebola outbreak using target capture experiments from fecal samples, and presents a list of candidate loci that may have facilitated their survival.