Psychiatric polygenic risk associates with cortical morphology and functional organization in aging

Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia

Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.

Cross-species comparative hippocampal transcriptomics in Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial pathology, with most cases having a sporadic origin. Recently, knock-in (KI) mouse models, such as the novel humanized amyloid-β (hAβ)-KI, have been developed to better resemble sporadic human AD.

METHODS

Here, we compared hippocampal publicly available transcriptomic profiles of transgenic (5xFAD and APP/PS1) and KI (hAβ-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients.

RESULTS

The three mouse models presented more Gene Ontology biological processes terms and enriched signaling pathways in common with LOAD than with EOAD individuals. Experimental validation of consistently dysregulated genes revealed five altered in mice (SLC11A1, S100A6, CD14, CD33, and C1QB) and three in humans (S100A6, SLC11A1, and KCNK). Finally, we identified 17 transcription factors potentially acting as master regulators of AD.

CONCLUSION

Our cross-species analyses revealed that the three mouse models presented a remarkable similarity to LOAD, with the hAβ-KI being the more specific one.

Molecular archaeology of human cognitive traits

The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.

Genome-wide DNA methylation profiles of autism spectrum disorder

OBJECTIVES

We aimed to identify differentially methylated genes and related signaling pathways in autism spectrum disorder (ASD).

METHODS

First, the DNA methylation profile in the brain samples (GSE131706 and GSE80017) and peripheral blood samples (GSE109905) was downloaded from the Gene Expression Omnibus database (GEO) dataset, followed by identification of differentially methylated genes and functional analysis. Second, the GSE109905 data set was used to further validate the methylation state and test the ability to diagnose disease of identified differentially methylated genes. Third, expression measurement of selected differentially methylated genes was performed in whole blood from an independent sample. Finally, protein-protein interaction (PPI) network of core differentially methylated genes was constructed.

RESULTS

Totally, 74 differentially methylated genes were identified in ASD, including 38 hypermethylated genes and 36 hypomethylated genes. 15 differentially methylated genes were further identified after validation in the GSE109905 data set. Among these, major histocompatibility complex (HLA)-DQA1 was involved in the molecular function of myosin heavy chain class II receptor activity; HLA-DRB5 was involved in the signaling pathways of cell adhesion molecules, Epstein-Barr virus infection and antigen processing and presentation. In the PPI analysis, the interaction pairs of HLA-DQA1 and HLA-DRB5, FMN2 and ACTR3, and CALCOCO2 and BAZ2B were identified. Interestingly, FMN2, BAZ2B, HLA-DRB5, CALCOCO2 and DUSP22 had a potential diagnostic value for patients with ASD. The expression result of four differentially methylated genes (HLA-DRB5, NTM, IL16 and COL5A3) in the independent sample was consistent with the integrated analysis.

CONCLUSIONS

Identified differentially methylated genes and enriched signaling pathway could be associated with ASD.

Chinese adult brain atlas with functional and white matter parcellation

Brain atlases play important roles in studying anatomy and function of the brain. As increasing interests in multi-modal magnetic resonance imaging (MRI) approaches, such as combining structural MRI, diffusion weighted imaging (DWI), and resting-state functional MRI (rs-fMRI), there is a need to construct integrated brain atlases based on these three imaging modalities. This study constructed a multi-modal brain atlas for a Chinese aging population (n = 180, age: 22–79 years), which consists of a T1 atlas showing the brain morphology, a high angular resolution diffusion imaging (HARDI) atlas delineating the complex fiber architecture, and a rs-fMRI atlas reflecting brain intrinsic functional organization in one stereotaxic coordinate. We employed large deformation diffeomorphic metric mapping (LDDMM) and unbiased diffeomorphic atlas generation to simultaneously generate the T1 and HARDI atlases. Using spectral clustering, we generated 20 brain functional networks from rs-fMRI data. We demonstrated the use of the atlas to explore the coherent markers among the brain morphology, functional networks, and white matter tracts for aging and gender using joint independent component analysis.

Measurement(s)	water content • water diffusion • blood oxygenation level-dependent signal
Technology Type(s)	Magnetic Resonance Imaging • Diffusion Tensor Imaging • Resting State Functional Connectivity Magnetic Resonance Imaging

Healthy aging: A bibliometric analysis of the literature

Due to dramatic growth of the aging population worldwide, there has been an urgent call for a public health strategy to manage healthy aging, with the ultimate goal being advancement of aging research. Considerable progress has been made in uncovering the mystery of aging process using multidisciplinary methods. There is a growing consensus in the field that aging traits which were originally thought to be disparate are likely to be interconnected. Thus, emerging research is needed to incorporate current findings of aging by building multiscale network models. This study reported the network of healthy aging research using bibliometric approaches. Based on the results, aging of the brain and muscle is a primary research focus which is a critical part of the multiscale network regulating the aging process. Among aging-associated diseases, Alzheimer's disease and frailty are among the main research focuses, and emerging work has focused on developing diagnostic tools for these diseases. For research on anti-aging interventions, calorie restriction, physical activity, and anti-aging pharmacology are the main interventions, of which the underlying mechanisms have been comprehensively studied in animal models.