Anxiety disorders affect roughly 40%–50% of people with Alzheimer's disease (AD), highlighting the need for treatments that address both cognition and emotional health. Cog-201, a gene therapy targeting the 5-HT2A receptor, has been shown in preclinical studies to improve memory and reduce anxiety. Analyses from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used to develop an unbiased, translational rationale for deploying Cog-201 to treat AD holistically, targeting cognition and anxiety together. Global cognition (MMSE), anxiety (NPI-A), overall neuropsychiatric symptom burden (NPI Total), amyloid PET burden, and serotonergic genotypes ( HTR2A rs6313; SLC6A4 rs25531) were analyzed using group comparisons and correlations, with visit-adjusted models for combined month-12 and month-24 observations. Across the whole ADNI cohort at month 12, higher NPI Total scores were significantly correlated with lower MMSE scores (r = −0.32), indicating that worsening neuropsychiatric symptoms, including anxiety and psychosis, accompany cognitive decline in AD. Higher neuropsychiatric symptom burden demonstrated a modest but statistically significant positive association with cortical amyloid burden measured using standardized ADNI UC Berkeley SUMMARY_SUVR values. Genotype-restricted analyses suggested that a serotonergic background may influence these relationships: the HTR2A rs6313 SNP (CT) showed a modest inverse association between MMSE and anxiety, and the SLC6A4 rs25531 (CC; within 5-HTTLPR) displayed a steeper negative slope. Taken with Cog-201’s preclinical profile, these results justify clinical evaluation of Cog-201 for AD with clinically relevant anxiety, advancing a holistic strategy that targets both cognition and neuropsychiatric symptoms. Exploratory genotype-stratified analyses suggested that serotonergic genetic background may influence these relationships; however, subgroup sizes were limited, and these findings should be interpreted cautiously. This study investigated whether anxiety severity is linked to poorer cognition, whether neuropsychiatric symptom burden is associated with cortical amyloid burden measured using standardized ADNI amyloid PET SUVR metrics, and whether common serotonergic variants influence these effects.

The emergence of the cognitive use of numbers and numerical systems is still poorly explored in prehistoric archeology and cognitive science. A few studies have investigated the topic based on alternative hypotheses, namely that a symbolic numerical thought emerged in a relatively recent past and is mostly culturally based or, on the contrary, that it is a biologically grounded trait as shown by a long evolutionary history that humans share in part with other animals. We hypothesize that evolutionary biological mechanisms and cultural learning are interacting with each other within the hominin clade, building the cognitive bases of our numerical thinking through a complex process that has required a long time to develop. We analyze exemplary findings from a not-abundant but still significant archaeological record that conveys numerical information, and that can be attributed not only to Homosapiens but also to earlier hominin species, Homo erectus and Homo neanderthalensis. We aim to show that transitioning from "quantical" numerosity (also defined as "the number sense": a perception of quantities we share with other non-human species) to cognitive numerical thinking requires an interplay of neural and molecular structures as biological prerequisites interacting with the cultural transmission. Our interpretation of the archaeological record and a biological-cultural process observed from Homo erectus to Homosapiens supports the hypothesis that the ability to use numerical concepts is part of a broader symbolic abstract cognition. In this context, the cognitive idea of number surpasses the mere "interpretation" of the meaning of the archaeological object. Archaeological artifacts possess structural, unintended properties that can acquire significance in contexts other than their original purpose (McLaughlin, 2014). (C) 2025 Published by Elsevier Masson SAS.

Chapter 6 provides an overview of the development of ancient DNA (aDNA) studies for Roman bioarchaeology. Viva and colleagues proceed to outline how both endogenous and exogenous aDNA research has been utilized in Roman contexts before presenting a case study in Roman archaeogenetic research from Pompeii. Through aDNA analysis of one individual from Pompeii, researchers reconstructed their genetic ancestry and confirmed that the individual was infected with tuberculosis at the time of death. The chapter concludes with a call to integrate multi-omic (genomic, epigenomic, and proteomic) approaches with more traditional osteological methods, especially paleopathology, in order to continue advancing the field of Roman bioarchaeology.

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Short hairpin RNAs (shRNA), targeting knockdown of specific genes, hold enormous promise for precision-based therapeutics to treat numerous neurodegenerative disorders. We designed an AAV9-shRNA targeting the downregulation of the 5-HT2A receptor, and recently demonstrated that intranasal delivery of this shRNA (referred to as COG-201), decreased anxiety and enhanced memory in mice and rats. In the current study, we provide additional in vivo data supporting a role of COG-201 in enhancing memory and functional in vitro data, whereby knockdown of the 5-HT2A receptor in primary mouse cortical neurons led to a significant decrease in mRNA expression (p = 0.0007), protein expression p-value = 0.0002, and in spontaneous electrical activity as measured by multielectrode array. In this regard, we observed a significant decrease in the number of spikes (p-value = 0.002), the mean firing rate (p-value = 0.002), the number of bursts (p-value = 0.015), and a decrease in the synchrony index (p-value = 0.005). The decrease in mRNA and protein expression, along with reduced spontaneous electrical activity in primary mouse cortical neurons, corroborate our in vivo findings and underscore the efficacy of COG-201 in decreasing HTR2A gene expression. This convergence of in vitro and in vivo evidence solidifies the potential of COG-201 as a targeted therapeutic strategy. The ability of COG-201 to decrease anxiety and enhance memory in animal models suggests that similar benefits might be achievable in humans. This could lead to the development of new treatments for conditions like generalized anxiety disorder, post-traumatic stress disorder (PTSD), and cognitive impairments associated with aging or neurodegenerative diseases.

Short-hairpin RNAs (shRNA), targeting knockdown of specific genes, hold enormous promise for precision-based therapeutics to treat numerous neurodegenerative disorders. However, whether shRNA constructed molecules can modify neuronal circuits underlying certain behaviors has not been explored. We designed shRNA to knockdown the human HTR2A gene in vitro using iPSC-differentiated neurons. Multi-electrode array (MEA) results showed that the knockdown of the 5HT-2A mRNA and receptor protein led to a decrease in spontaneous electrical activity. In vivo, intranasal delivery of AAV9 vectors containing shRNA resulted in a decrease in anxiety-like behavior in mice and a significant improvement in memory in both mice (104%) and rats (92%) compared to vehicle-treated animals. Our demonstration of a non-invasive shRNA delivery platform that can bypass the blood–brain barrier has broad implications for treating numerous neurological mental disorders. Specifically, targeting the HTR2A gene presents a novel therapeutic approach for treating chronic anxiety and age-related cognitive decline.

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We performa genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimagingstudies showthat 17 variants affect specificbrain areas, butmost have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Background:Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods:We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results:Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions:Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

Individuals with schizophrenia (SZ) show aberrant activations, assessed via functional magnetic resonance imaging (fMRI), during auditory oddball tasks. However, associations with cognitive performance and genetic contributions remain unknown. This study compares individuals with SZ to healthy volunteers (HVs) using two cross-sectional data sets from multi-center brain imaging studies. It examines brain activation to auditory oddball targets, and their associations with cognitive domain performance, schizophrenia polygenic risk scores (PRS), and genetic variation (loci). Both sample 1 (137 SZ vs. 147 HV) and sample 2 (91 SZ vs. 98 HV), showed hypoactivation in SZ in the left-frontal pole, and right frontal orbital, frontal pole, paracingulate, intracalcarine, precuneus, supramarginal and hippocampal cortices, and right thalamus. In SZ, precuneus activity was positively related to cognitive performance. Schizophrenia PRS showed a negative correlation with brain activity in the right-supramarginal cortex. GWA analyses revealed significant single-nucleotide polymorphisms associated with right-supramarginal gyrus activity. RPL36 also predicted right-supramarginal gyrus activity. In addition to replicating hypoactivation for oddball targets in SZ, this study identifies novel relationships between regional activity, cognitive performance, and genetic loci that warrant replication, emphasizing the need for continued data sharing and collaborative efforts.

Transposable elements (TEs) are mobile genetic elements that constitute half of the human genome. Recent studies suggest that polymorphic non-reference TEs (nrTEs) may contribute to cognitive diseases, such as schizophrenia, through a cis-regulatory effect. The aim of this work is to identify sets of nrTEs putatively linked to an increased risk of developing schizophrenia. To do so, we inspected the nrTE content of genomes from the dorsolateral prefrontal cortex of schizophrenic and control individuals and identified 38 nrTEs that possibly contribute to the emergence of this psychiatric disorder, two of them further confirmed with haplotype-based methods. We then performed in silico functional inferences and found that 9 of the 38 nrTEs act as expression/alternative splicing quantitative trait loci (eQTLs/sQTLs) in the brain, suggesting a possible role in shaping the human cognitive genome structure. To our knowledge, this is the first attempt at identifying polymorphic nrTEs that can contribute to the functionality of the brain. Finally, we suggest that a neurodevelopmental genetic mechanism, which involves evolutionarily young nrTEs, can be key to understanding the ethio-pathogenesis of this complex disorder.

Abstract The increase of brain dimensions and complexity has characterized the evolution of the genus Homo. According to the available fossil and genetic evidence, a crucial stage came before the divergence of Neanderthals, Denisovans and Homo sapiens , during the Middle Pleistocene. We consider a specimen of about 400 ka, whose phenotype is at the roots of this divergence: Ceprano calvarium (Italy). Here, we show a derived cerebrovascular organization with a mosaic of modern human and primitive features characteristics. Computed microtomography shows vascular variation and ontogenetic defects associated with ventricular and lymphatic involvement while phylogenetic analyzes highlight a dysregulation of the Tet1 gene that shows an accelerated mutation rate between 1.2 Ma and 466 ka, in contrast with the expected neutral evolution of the human genome. These results shed light on the dynamics of cranio-cerebral growth during the encephalization process and on the cerebral vascular and lymphatic system involved in this process. The results of this study could have implications for the research of many of the diseases of the central nervous system that have become predominant in an increasingly structured and long-lived brain system such as that of modern Homo sapiens .

Background and Hypothesis Schizophrenia (SZ) and bipolar disorder (BD) share genetic risk factors, yet patients display differential levels of cognitive impairment. We hypothesized a genome-transcriptome-functional connectivity (frontoparietal)-cognition pathway linked to SZ-versus-BD differences, and conducted a multiscale study to delineate this pathway. Study Designs Large genome-wide studies provided single nucleotide polymorphisms (SNPs) conferring more risk for SZ than BD, and we identified their regulated genes, namely SZ-biased SNPs and genes. We then (a) computed the polygenic risk score for SZ (PRSSZ) of SZ-biased SNPs and examined its associations with imaging-based frontoparietal functional connectivity (FC) and cognitive performances; (b) examined the spatial correlation between ex vivo postmortem expressions of SZ-biased genes and in vivo, SZ-related FC disruptions across frontoparietal regions; (c) investigated SZ-versus-BD differences in frontoparietal FC; and (d) assessed the associations of frontoparietal FC with cognitive performances. Study Results PRSSZ of SZ-biased SNPs was significantly associated with frontoparietal FC and working memory test scores. SZ-biased genes' expressions significantly correlated with SZ-versus-BD differences in FC across frontoparietal regions. SZ patients showed more reductions in frontoparietal FC than BD patients compared to controls. Frontoparietal FC was significantly associated with test scores of multiple cognitive domains including working memory, and with the composite scores of all cognitive domains. Conclusions Collectively, these multiscale findings support the hypothesis that SZ-biased genetic risk, through transcriptome regulation, is linked to frontoparietal dysconnectivity, which in turn contributes to differential cognitive deficits in SZ-versus BD, suggesting that potential biomarkers for more precise patient stratification and treatment.

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer’s disease (LOAD) over a relatively short period of time (12–48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

Neanderthals are characterised by the largest brains of the Homo species. In addition to their large size, the Neanderthal brains present a peculiar elongated shape, which is markedly contrasting with the globular brain shape of Homo sapiens, due to the relative increase—or lack thereof—of specific brain regions such as the parietal lobe and the cerebellum (CB). A joint analysis of the anatomical data of the Neanderthal brain, the neural genes controlling for the evolution of the brain and the interpretation of the archaeological record of neanderthalian sites suggest that Neanderthals had a well-developed cognition, although probably different from that of H. sapiens. Some engraved stones, evidence of a complex behaviour and the not utilitarian use of molluscs, sometimes treated with ochre, are relevant to the debate on Neanderthal cognition and aesthetic structure. The engraved stones belong to a very simple graphic repertoire involving the combination of several lines on a surface, in variable but conceptually homogeneous patterns known from various Neanderthal contexts. All the evidence is part of a repertoire found in Neanderthal sites. They are characterised by conceptual procedures of varying complexity, which make them something more than merely utilitarian products. Instead, they are pertinent to the debate on the origin of the sense of beauty, and they represent the first unequivocal signs of a visual culture, both landmarks of an advanced and well-developed cognition.

The archaeological site of Pompeii is one of the 54 UNESCO World Heritage sites in Italy, thanks to its uniqueness: the town was completely destroyed and buried by a Vesuvius' eruption in 79 AD. In this work, we present a multidisciplinary approach with bioarchaeological and palaeogenomic analyses of two Pompeian human remains from the Casa del Fabbro. We have been able to characterize the genetic profile of the first Pompeian' genome, which has strong affinities with the surrounding central Italian population from the Roman Imperial Age. Our findings suggest that, despite the extensive connection between Rome and other Mediterranean populations, a noticeable degree of genetic homogeneity exists in the Italian peninsula at that time. Moreover, palaeopathological analyses identified the presence of spinal tuberculosis and we further investigated the presence of ancient DNA from Mycobacterium tuberculosis. In conclusion, our study demonstrates the power of a combined approach to investigate ancient humans and confirms the possibility to retrieve ancient DNA from Pompeii human remains. Our initial findings provide a foundation to promote an intensive and extensive paleogenetic analysis in order to reconstruct the genetic history of population from Pompeii, a unique archaeological site.

Background: Altered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer’s disease (AD) and in AD patient plasma samples. Objective: This study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138). Methods: Specimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods. Results: Total plasma SM levels were not significantly affected by age or cognitive status. However, one metabolite that has been elevated in manifest AD in several recent studies, SM OHC14:1, was reduced significantly in pre-clinical AD and MCI relative to normal controls. Conclusion: We recommend additional comprehensive plasma lipidomics in experimental and clinical biospecimens related to LOAD that might advance the utility of plasma sphingomyelin levels in molecular phenotyping and interpretations of pathobiological mechanisms.

Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features for schizophrenia (SZ) case-control classification. An L0 -norm regularization is implemented on the input layer of the network for sparse feature selection, which can later be interpreted based on importance weights. We applied the proposed approach on a large multi-study cohort with gray matter volume (GMV) and single nucleotide polymorphism (SNP) data for SZ classification. A total of 634 individuals served as training samples, and the classification model was evaluated for generalizability on three independent datasets of different scanning protocols (N = 394, 255, and 160, respectively). We examined the classification power of pure GMV features, as well as combined GMV and SNP features. Empirical experiments demonstrated that sparse DNN slightly outperformed independent component analysis + support vector machine (ICA + SVM) framework, and more effectively fused GMV and SNP features for SZ discrimination, with an average error rate of 28.98% on external data. The importance weights suggested that the DNN model prioritized to select frontal and superior temporal gyrus for SZ classification with high sparsity, with parietal regions further included with lower sparsity, echoing previous literature. The results validate the application of the proposed approach to SZ classification, and promise extended utility on other data modalities and traits which ultimately may result in clinically useful tools.