Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes

HIV and Low Omega-3 Levels May Heighten Hippocampal Volume Differences Between Men and Women With Substance Use

Background

Sex differences in hippocampal volumes are well-documented, but their interaction with HIV status and omega-3 fatty acids-particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)-remains unclear, especially in underserved populations. This study examines how HIV and omega-3 fatty acids influence sex differences in hippocampal volume and explores whether cognitive performance related to episodic memory modifies the association of omega-3 levels with hippocampal volume, considering both HIV status and sex.

Methods

We enrolled 166 participants aged over 45 years from a Baltimore, Maryland cohort. Brain MRIs were performed using a 3.0-T Siemens scanner, and volumetric segmentation was conducted with FreeSurfer (version 6.0), adjusting for intracranial volume (ICV).

Results

Our study found that: (1) Among HIV-negative participants, females had significantly lower hippocampal volumes than males in 1 of 26 regions, whereas HIV-positive females had lower volumes in 13 of 26 regions (p < 0.006 for HIV-negative vs. HIV-positive females), (2) In HIV-positive individuals with EPA levels ≤0.40 %, females exhibited lower volumes in 11 of 26 regions, compared to no differences in those with EPA levels >0.40 % (p = 0.0003 for ≤0.40 % vs. >0.40 %), (3) Across all participants, lower EPA and DHA levels were associated with greater sex differences in hippocampal volumes, which diminished or disappeared at higher EPA and DHA levels (p < 0.00001 for EPA ≤0.40 % vs. >0.40 %; p = 0.004 for DHA ≤2.0 % vs. >2.0 %), and (4) Among Adults with lower episodic memory, higher log-scaled EPA levels were independently associated with greater hippocampal volume.

Conclusions

HIV may amplify sex differences in hippocampal volumes, disproportionately affecting females. Higher EPA and DHA levels may mitigate these effects, suggesting a protective role against hippocampal atrophy. Further studies are warranted to confirm these findings and explore whether the benefits extend to males with HIV or individuals without HIV.

Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study

BACKGROUND

The swift rise in the prevalence of Alzheimer's disease (AD) alongside its significant societal and economic impact has created a pressing demand for effective interventions and treatments. However, there are no available treatments that can modify the progression of the disease.

METHODS

Eight AD brain tissues datasets and three blood datasets were obtained. Consensus clustering was utilized as a method to discern the various subtypes of AD. Then, module genes were screened using weighted correlation network analysis (WGCNA). Furthermore, screening hub genes was conducted through machine-learning analyses. Finally, A comprehensive analysis using a systematic approach to druggable genome-wide Mendelian randomization (MR) was conducted.

RESULTS

Two AD subclasses were identified, namely cluster.A and cluster.B. The levels of gamma secretase activity, beta secretase activity, and amyloid-beta 42 were found to be significantly elevated in patients classified within cluster A when compared to those in cluster B. Furthermore, by utilizing the differentially expressed genes shared among these clusters, along with identifying druggable genes and applying WGCNA to these subtypes, we were able to develop a scoring system referred to as DG.score. This scoring system has demonstrated remarkable predictive capability for AD when evaluated against multiple datasets. Besides, A total of 30 distinct genes that may serve as potential drug targets for AD were identified across at least one of the datasets investigated, whether derived from brain samples or blood analyses. Among the identified genes, three specific candidates that are considered druggable (LIMK2, MAPK8, and NDUFV2) demonstrated significant expression levels in both blood and brain tissues. Furthermore, our research also revealed a potential association between the levels of LIMK2 and concentrations of CSF Aβ (OR 1.526 (1.155-2.018)), CSF p-tau (OR 1.106 (1.024-01.196)), and hippocampal size (OR 0.831 (0.702-0.948)).

CONCLUSIONS

This study provides a notable advancement to the existing literature by offering genetic evidence that underscores the potential therapeutic advantages of focusing on the druggable gene LIMK2 in the treatment of AD. This insight not only contributes to our understanding of AD but also guides future drug discovery efforts.

Structural alteration of hippocampal subfields in type 2 diabetes mellitus patients with dyslipidemia

OBJECTIVE

To explore alterations in hippocampal subfield volumes in type 2 diabetes mellitus (T2DM) patients with dyslipidemia using hippocampal subfield segmentation.

METHODS

A total of 99 T2DM patients were prospectively recruited and divided into two groups based on the presence or absence of dyslipidemia: the T2DM dyslipidemia group and the T2DM normal lipidemia group. Additionally, 57 healthy volunteers were recruited as the healthy control (HC) group. General clinical data and cognitive psychological scale scores were collected. Subgroup analyses of T2DM patients were conducted based on the presence or absence of mild cognitive impairment (MCI). Hippocampal subfield volumes were analyzed using a general linear model with post-hoc Bonferroni correction. Significant differential hippocampal subfields were further analyzed in subgroups using the general linear model with post-hoc Bonferroni tests. Partial correlation analyses were performed to assess correlations between subfield-specific volumes and lipid and glucose metabolism indicators, as well as cognitive psychological scale scores. P-values from partial correlation analyses were corrected using the false discovery rate (FDR).

RESULTS

Volumes of the bilateral hippocampal tail, left presubiculum_body, and right subiculum_body were significantly reduced in the T2DM dyslipidemia group compared to both the HC group and the T2DM normal lipidemia group. Post-hoc analyses revealed that the T2DM dyslipidemia group had the smallest hippocampal subfield volumes. Further subgroup analysis showed that T2DM dyslipidemia patients with MCI exhibited the most pronounced volume reductions in the bilateral hippocampal tail and right subiculum_body. After FDR correction, partial correlation analysis indicated that, in the T2DM dyslipidemia group, the left hippocampal tail volume was positively correlated with the Montreal Cognitive Assessment score. In the T2DM dyslipidemia without MCI group, the volume of the right subiculum_body was negatively correlated with fasting insulin levels and the insulin resistance index, but positively correlated with total cholesterol and low-density lipoprotein cholesterol levels. In T2DM patients with normal lipidemia without MCI, the volume of the right subiculum_body was positively correlated with TC levels.

CONCLUSION

T2DM patients with dyslipidemia, especially those with MCI, exhibit significant atrophy in hippocampal subfield volumes, with correlations observed between lipid levels and hippocampal subfield volume changes. These findings suggest that lipid alterations may play an essential role in hippocampal structural abnormalities and cognitive impairment in T2DM patients. This study provides new insights into the neuropathophysiological mechanisms underlying brain alterations and cognitive decline in T2DM.

Hippocampal gray matter volume alterations in patients with first-episode and recurrent major depressive disorder and their associations with gene profiles

BACKGROUND

Recent studies indicate that patients with first-episode drug-naïve (FEDN) and recurrent major depressive disorder (R-MDD) exhibit distinct atrophy patterns in the hippocampal subregions along the proximal-distal axis. However, it remains unclear whether such differences occur along the long axis and how they may relate to specific genes.

METHODS

In the present study, we analyzed T1-weighted images from 421 patients (FEDN: n = 232; R-MDD: n = 189) and 544 normal controls (NC) as part of the REST-meta-MDD consortium. Additionally, transcriptome maps and structural Magnetic Resonance Imaging (MRI) data of six donated brains were obtained from the Allen Human Brain Atlas (AHBA). We first identified changes in gray matter volume (GMV) within the hippocampus of both FEDN and R-MDD patients and then integrated these findings with AHBA transcriptome data to investigate the genes associated with hippocampal GMV changes.

RESULTS

Compared to NC, FEDN patients displayed reduced GMV in the left hippocampal tail, whereas R-MDD patients exhibited decreased GMV in the bilateral hippocampal body and increased GMV in the bilateral hippocampal tail. Further analysis revealed that expression levels of SYTL2 positively correlated with GMV changes in the hippocampus of FEDN patients, while SORCS3 and SLIT2 positively correlated with those in R-MDD.

CONCLUSIONS

Our results suggest that GMV alterations in hippocampal subfields along the long axis differ between FEDN and R-MDD, reflecting progressive hippocampal deterioration with prolonged depression, potentially supported by the expression of specific genes. These findings offer valuable insights into the distinct neural and genetic mechanisms underlying FEDN and R-MDD, which may aid in the development of more targeted and effective treatment strategies for MDD subtypes.

Genetic Predisposition to Hippocampal Atrophy and Risk of Amnestic Mild Cognitive Impairment and Alzheimer's Dementia

BACKGROUND

There is a paucity of evidence on the association between genetic propensity for hippocampal atrophy with cognitive outcomes. Therefore, we examined the relationship of the polygenic risk score for hippocampal atrophy (PRShp) with the incidence of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) as well as the rates of cognitive decline.

METHODS

Participants were drawn from the population-based HELIAD cohort. Comprehensive neuropsychological assessments were performed at baseline and at follow-up. PRShp was derived from the summary statistics of a large genome-wide association study for hippocampal volume. Cox proportional hazards models as well as generalized estimating equations (GEEs) were used to evaluate the association of PRShp with the combined incidence of aMCI/AD and cognitive changes over time, respectively. All models were adjusted for age, sex, education, and apolipoprotein E (APOE) genotype.

RESULTS

Our analysis included 618 older adults, among whom 73 developed aMCI/AD after an average follow-up of 2.96 ± 0.8 years. Each additional SD of PRShp elevated the relative hazard for incident aMCI/AD by 46%. Participants at the top quartile of PRShp had an almost three times higher risk of converting to aMCI/AD compared to the lowest quartile group. Higher PRShp scores were also linked to steeper global cognitive and memory decline. The impact of PRShp was greater among women and younger adults.

CONCLUSIONS

Our findings support the association of PRShp with aMCI/AD incidence and with global cognitive and memory decline over time. The PRS association was sex- and age-dependent, suggesting that these factors should be considered in genetic modelling for AD.

TESC overexpression mitigates amyloid-β-induced hippocampal atrophy and memory decline

BACKGROUND AND OBJECTIVES

Genome-wide association studies (GWASs) have identified numerous candidate genes for human brain-imaging phenotypes; however, the biological relevance of many of these genes remains unconfirmed. This study aimed to investigate the causal relationships among tescalcin (TESC) (a GWAS-indicated gene), hippocampal volume, Alzheimer's disease (AD), and the underlying biological mechanisms.

METHODS

Human transcriptional data were analyzed to confirm relative TESC expression in the hippocampus. In cell experiments, RNA-seq analysis was used to identify the potential biological pathways for TESC overexpression, and immunofluorescence imaging and cell viability assays were used to evaluate the effect of TESC overexpression on neuronal structure and survival. In animal experiments, the effects of TESC overexpression on hippocampal volume and cognitive function in normal mice and amyloid-β (Aβ)-induced AD mice were investigated by 9.4 T magnetic resonance imaging and behavioral tests. Underlying mechanisms were further assessed via western blotting and electrophysiological recordings.

RESULTS

Human transcriptional data demonstrated that TESC is primarily expressed in the hippocampus and neurons. TESC overexpression enhanced the viability of HT22 cells and reduced Aβ-induced cell death. In mouse models, Tesc-overexpressing mice revealed increased hippocampal volume, likely owing to enhanced cell viability and long-term potentiation (LTP), and reducing apoptotic- and oxidation-induced hippocampal damage. TESC overexpression could significantly mitigate Aβ-induced hippocampal atrophy and memory impairment, potentially by reducing Aβ-induced neuronal apoptosis and LTP weakening.

CONCLUSION

This study exemplifies the translation of GWAS findings into actionable biological knowledge and suggests that upregulation of TESC may offer a promising therapeutic strategy for AD.

Large-scale brainstem neuroimaging and genetic analyses provide new insights into the neuronal mechanisms of hypertension

While brainstem regions are central regulators of blood pressure, the neuronal mechanisms underlying their role in hypertension remain poorly understood. Here, we investigated the structural and genetic relationships between global and regional brainstem volumes and blood pressure. We used magnetic resonance imaging data from n = 32,666 UK Biobank participants, and assessed the association of volumes of the whole brainstem and its main regions with blood pressure. We applied powerful statistical genetic tools, including bivariate causal mixture modeling (MiXeR) and conjunctional false discovery rate (conjFDR), to non-overlapping genome-wide association studies of brainstem volumes (n = 27,034) and blood pressure (n = 321,843) in the UK Biobank cohort. We observed negative associations between the whole brainstem and medulla oblongata volumes and systolic blood and pulse pressure, and positive relationships between midbrain and pons volumes and blood pressure traits when adjusting for the whole brainstem volume (all partial correlation coefficients ∣r∣ effects between 0.03 and 0.05, p ≤ 0.0042). We observed the largest genetic overlap for the whole brainstem, sharing 77% of its trait-influencing variants with blood pressure. We identified 65 shared loci between brainstem volumes and blood pressure traits and mapped these to 71 genes, implicating molecular pathways linked to sympathetic nervous system development, metal ion transport, and vascular homeostasis. The present findings support a link between brainstem structures and blood pressure and provide insights into their shared genetic underpinnings. The overlapping genetic architectures and mapped genes offer mechanistic information about the roles of brainstem regions in hypertension.

Multiscale Analysis Reveals Hippocampal Subfield Vulnerabilities to Chronic Cortisol Overexposure: Evidence From Cushing's Disease

BACKGROUND

Chronic cortisol overexposure plays a significant role in the development of neuropathological changes associated with neuropsychiatric and neurodegenerative disorders. The hippocampus, the primary target of cortisol, may exhibit characteristic regional responses due to its internal heterogeneity. In this study, we explored structural and functional alterations of hippocampal (HP) subfields in Cushing's disease (CD), an endogenous model of chronic cortisol overexposure.

METHODS

Utilizing structural and resting-state functional magnetic resonance imaging data from 169 participants (86 patients with CD and 83 healthy control participants [HCs]) recruited from a single center, we investigated specific structural changes in HP subfields and explored the functional connectivity alterations driven by these structural abnormalities. We also analyzed potential associative mechanisms between these changes and biological attributes, neuropsychiatric representations, cognitive function, and gene expression profiles.

RESULTS

Compared with HCs, patients with CD exhibited significant bilateral volume reductions in multiple HP subfields. Notably, volumetric decreases in the left HP body and tail subfields were significantly correlated with cortisol levels, Montreal Cognitive Assessment scores, and quality of life measures. Disrupted connectivity between the structurally abnormal HP subfields and the ventromedial prefrontal cortex may impair reward-based decision making and emotional regulation, with this dysconnectivity being linked to structural changes in right HP subfields. Another region that exhibited dysconnectivity was located in the left pallidum and putamen. Gene expression patterns associated with synaptic components may underlie these macrostructural alterations.

CONCLUSIONS

Our findings elucidate the subfield-specific effects of chronic cortisol overexposure on the hippocampus, enhancing understanding of shared neuropathological traits linked to cortisol dysregulation in neuropsychiatric and neurodegenerative disorders.

It Takes Three: Parental Hostility, Brain Morphology, and Child Externalizing Problems in a Parent-Offspring Neuroimaging Trio Design

Hostility often co-occurs in parents and associates with increased aggression and inattention problems in children. In this population-based cohort of 484 mother-father-child neuroimaging trios, we investigated the degree to which associations of prenatal and childhood parental hostility would be associated with maternal, paternal, and child brain structural differences. Also, we examined whether hippocampal volumes of the parents or child mediate the association of prenatal parental hostility with child externalizing behaviors. Maternal and paternal hostility was assessed with the hostility subscale of the Brief Symptom Inventory at three time points: prenatally at 30 weeks' gestation and when the child was 3 and 10 years old. During adolescence assessment wave (age 14), maternal, paternal, and offspring assessment included a magnetic resonance imaging. Child externalizing problems were assessed with Youth Self-Report Child Behavior Checklist. Our findings suggest that maternal and paternal hostility were each associated with smaller gray matter, white matter, and hippocampal volumes of their own and their partner's brain. Prenatal maternal but not paternal hostility was associated with smaller total gray matter, white matter, and hippocampal volumes in the offspring. The child's hippocampal volumes partially mediated the associations of prenatal parental hostility (latent construct) with adolescent externalizing behavior, even after adjusting for prior child externalizing problems. Moreover, parental psychopathology may have long-lasting neurodevelopmental correlates in children that underlie the intergenerational transmission of behavioral problems. The behavior of family members results from a system of interdependent dyadic relationships over time that associate with specific brain structural differences.

Structural and functional alterations of the hippocampal subfields in T2DM with mild cognitive impairment and insulin resistance: A prospective study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance (IR) and is often accompanied by mild cognitive impairment (MCI). The detrimental effects of T2DM and IR on the hippocampus have been extensively demonstrated. Few studies have examined the effects of IR on structure and function of hippocampal subfields in T2DM-MCI patients.

METHOD

A total of 104 T2DM patients were recruited in this prospective study and divided into four groups (T2DM-MCI-higherIR, n = 17; T2DM-MCI-lowerIR, n = 32; T2DM-nonMCI-higherIR, n = 19; T2DM-nonMCI-lowerIR, n = 36). Structure and function MRI data were captured. Clinical variables and neuropsychological scores were determined for all participants. Hippocampal subfield volume and functional connectivity were compared among four groups. Partial correlation analysis was performed between imaging indicators, clinical variables, and neuropsychological scores in all patients.

RESULTS

T2DM-MCI-higher IR group had the smallest volumes of bilateral hippocampal tail, right subiculum-body, right GC-ML-DG-body, and right CA4-body. IR in right hippocampal tail, right subiculum-body, and right GC-ML-DG-body exerted main effect. Furthermore, elevated functional connectivity was found between right subiculum-body and bilateral dorsolateral prefrontal cortex and right anterior cingulate-medial prefrontal cortex. Hippocampal subfield volume positively correlates with total cholesterol and triglycerides and negatively correlates with fasting insulin.

CONCLUSION

The present study found that T2DM-MCI patients have structural and functional alterations in hippocampal subfields, and IR is a negative factor influencing the alteration of hippocampal subfields volume. These findings support the importance of IR in T2DM-MCI patients and might be potential neuroimaging biomarkers of cerebral impairment in T2DM-MCI patients.

Genetic architectures of the human hippocampus and those involved in neuropsychiatric traits

BACKGROUND

The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus's high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential.

METHODS

We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits.

RESULTS

Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10-9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P < 0.05/240), revealing 433 pleiotropic loci. Particularly, genes like ACBD4, ARHGAP27, KANSL1, MAPT, ARL17A, and ARL17B were involved in over 50 HASV-neuropsychiatric pairs. Leveraging Mendelian randomization analysis, we further confirmed that atrophy in the left hippocampus, right hippocampus, right hippocampal body, and right CA1-3 region were associated with an increased risk of developing Parkinson's disease (PD). Furthermore, PRS for all four HASVs were significantly linked to a higher risk of Parkinson's disease (PD), with the highest hazard ratio (HR) of 1.30 (95% CI 1.18-1.43, P = 6.15 × 10⁻⁸) for right hippocampal volume.

CONCLUSIONS

These findings highlight the extensive distribution of pleiotropic genetic determinants between HASVs and neuropsychiatric traits. Moreover, they suggest a significant potential for effectively managing and intervening in these diseases during their early stages.

Genome-wide association study meta-analysis of neurofilament light (NfL) levels in blood reveals novel loci related to neurodegeneration

Neurofilament light chain (NfL) levels in circulation have been established as a sensitive biomarker of neuro-axonal damage across a range of neurodegenerative disorders. Elucidation of the genetic architecture of blood NfL levels could provide new insights into molecular mechanisms underlying neurodegenerative disorders. In this meta-analysis of genome-wide association studies (GWAS) of blood NfL levels from eleven cohorts of European ancestry, we identify two genome-wide significant loci at 16p12 (UMOD) and 17q24 (SLC39A11). We observe association of three loci at 1q43 (FMN2), 12q14, and 12q21 with blood NfL levels in the meta-analysis of African-American ancestry. In the trans-ethnic meta-analysis, we identify three additional genome-wide significant loci at 1p32 (FGGY), 6q14 (TBX18), and 4q21. In the post-GWAS analyses, we observe the association of higher NfL polygenic risk score with increased plasma levels of total-tau, Aβ-40, Aβ-42, and higher incidence of Alzheimer's disease in the Rotterdam Study. Furthermore, Mendelian randomization analysis results suggest that a lower kidney function could cause higher blood NfL levels. This study uncovers multiple genetic loci of blood NfL levels, highlighting the genes related to molecular mechanism of neurodegeneration.

Longitudinal study on hippocampal subfields and glucose metabolism in early psychosis

Altered hippocampal morphology and metabolic pathology, but also hippocampal circuit dysfunction, are established phenomena seen in psychotic disorders. Thus, we tested whether hippocampal subfield volume deficits link with deviations in glucose metabolism commonly seen in early psychosis, and whether the glucose parameters or subfield volumes change during follow-up period using one-year longitudinal study design of 78 first-episode psychosis patients (FEP), 48 clinical high-risk patients (CHR) and 83 controls (CTR). We also tested whether hippocampal morphology and glucose metabolism relate to clinical outcome. Hippocampus subfields were segmented with Freesurfer from 3T MRI images and parameters of glucose metabolism were determined in fasting plasma samples. Hippocampal subfield volumes were consistently lower in FEPs, and findings were more robust in non-affective psychoses, with strongest decreases in CA1, molecular layer and hippocampal tail, and in hippocampal tail of CHRs, compared to CTRs. These morphometric differences remained stable at one-year follow-up. Both non-diabetic CHRs and FEPs had worse glucose parameters compared to CTRs at baseline. We found that, insulin levels and insulin resistance increased during the follow-up period only in CHR, effect being largest in the CHRs converting to psychosis, independent of exposure to antipsychotics. The worsening of insulin resistance was associated with deterioration of function and symptoms in CHR. The smaller volume of hippocampal tail was associated with higher plasma insulin and insulin resistance in FEPs, at the one-year follow-up. Our longitudinal study supports the view that temporospatial hippocampal subfield volume deficits are stable near the onset of first psychosis, being more robust in non-affective psychoses, but less prominent in the CHR group. Specific subfield defects were related to worsening glucose metabolism during the progression of psychosis, suggesting that hippocampus is part of the circuits regulating aberrant glucose metabolism in early psychosis. Worsening of glucose metabolism in CHR group was associated with worse clinical outcome measures indicating a need for heightened clinical attention to metabolic problems already in CHR.

Exploring volumetric abnormalities in subcortical L-HPA axis structures in pediatric generalized anxiety disorder

BACKGROUND

Pediatric generalized anxiety disorder (GAD) is debilitating and increasingly prevalent, yet its etiology remains unclear. Some believe the disorder to be propagated by chronic dysregulation of the limbic-hypothalamic-pituitary-adrenal (L-HPA) axis, but morphometric studies of implicated subcortical areas have been largely inconclusive. Recognizing that certain subcortical subdivisions are more directly involved in L-HPA axis functioning, this study aims to detect specific abnormalities in these critical areas.

METHODS

Thirty-eight MRI scans of preschool children with (n = 15) and without (n = 23) GAD underwent segmentation and between-group volumetric comparisons of the basolateral amygdala (BLA), ventral hippocampal subiculum (vSC), and mediodorsal medial magnocellular (MDm) area of the thalamus.

RESULTS

Children with GAD displayed significantly larger vSC compared to healthy peers, F(1, 31) = 6.50, pFDR = .048. On average, children with GAD presented with larger BLA and MDm, Fs(1, 31) ≥ 4.86, psFDR ≤ .054. Exploratory analyses revealed right-hemispheric lateralization of all measures, most notably the MDm, F(1, 31) = 8.13, pFDR = .024, the size of which scaled with symptom severity, r = .83, pFDR = .033.

CONCLUSION

The BLA, vSC, and MDm are believed to be involved in the regulation of anxiety and stress, both individually and collectively through the excitation and inhibition of the L-HPA axis. All were found to be enlarged in children with GAD, perhaps reflecting hypertrophy related to hyperexcitability, or early neuronal overgrowth. Longitudinal studies should investigate the relationship between these early morphological differences and the long-term subcortical atrophy previously observed.

FPLS-DC: functional partial least squares through distance covariance for imaging genetics

MOTIVATION

Imaging genetics integrates imaging and genetic techniques to examine how genetic variations influence the function and structure of organs like the brain or heart, providing insights into their impact on behavior and disease phenotypes. The use of organ-wide imaging endophenotypes has increasingly been used to identify potential genes associated with complex disorders. However, analyzing organ-wide imaging data alongside genetic data presents two significant challenges: high dimensionality and complex relationships. To address these challenges, we propose a novel, nonlinear inference framework designed to partially mitigate these issues.

RESULTS

We propose a functional partial least squares through distance covariance (FPLS-DC) framework for efficient genome wide analyses of imaging phenotypes. It consists of two components. The first component utilizes the FPLS-derived base functions to reduce image dimensionality while screening genetic markers. The second component maximizes the distance correlation between genetic markers and projected imaging data, which is a linear combination of the FPLS-basis functions, using simulated annealing algorithm. In addition, we proposed an iterative FPLS-DC method based on FPLS-DC framework, which effectively overcomes the influence of inter-gene correlation on inference analysis. We efficiently approximate the null distribution of test statistics using a gamma approximation. Compared to existing methods, FPLS-DC offers computational and statistical efficiency for handling large-scale imaging genetics. In real-world applications, our method successfully detected genetic variants associated with the hippocampus, demonstrating its value as a statistical toolbox for imaging genetic studies.

AVAILABILITY AND IMPLEMENTATION

The FPLS-DC method we propose opens up new research avenues and offers valuable insights for analyzing functional and high-dimensional data. In addition, it serves as a useful tool for scientific analysis in practical applications within the field of imaging genetics research. The R package FPLS-DC is available in Github: https://github.com/BIG-S2/FPLSDC.

Genetic architecture of hippocampus subfields volumes in Alzheimer's disease

BACKGROUND

The hippocampus is a heterogeneous structure, comprising histologically and functionally distinguishable hippocampal subfields. The volume reductions in hippocampal subfields have been demonstrated to be linked with Alzheimer's disease (AD). The aim of our study is to investigate the hippocampal subfields' genetic architecture based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set.

METHODS

After preprocessing the downloaded genetic variants and imaging data from the ADNI database, a co-sparse reduced rank regression model was applied to analyze the genetic architecture of hippocampal subfields volumes. Homology modeling, docking, molecular dynamics simulations, and Co-IP experiments for protein-protein interactions were used to verify the function of target protein on hippocampal subfields successively. After that, the association analysis between the candidated genes on the hippocampal subfields volume and clinical scales were performed.

RESULTS

The results of the association analysis revealed five unique genetic variants (e.g., ubiquitin-specific protease 10 [USP10]) changed in nine hippocampal subfields (e.g., the granule cell and molecular layer of the dentate gyrus [GC-ML-DG]). Among five genetic variants, USP10 had the strongest interaction effect with BACE1, which affected hippocampal subfields verified by MD and Co-IP experiments. The results of association analysis between the candidated genes on the hippocampal subfields volume and clinical scales showed that candidated genes influenced the volume and function of hippocampal subfields.

CONCLUSIONS

Current evidence suggests that hippocampal subfields have partly distinct genetic architecture and may improve the sensitivity of the detection of AD.

Shared and unique heritability of hippocampal subregion volumes in children and adults

Behavioral genetic analyses have not demonstrated robust, unique, genetic correlates of hippocampal subregion volume. Genetic differentiation of hippocampal longitudinal axis subregion volume has not yet been investigated in population-based samples, although this has been demonstrated in rodent and post-mortem human tissue work. The following study is the first population-based investigation of genetic factors that contribute to gray matter volume along the hippocampal longitudinal axis. Twin-based biometric analyses demonstrated that longitudinal axis subregions are associated with significant, unique, genetic variance, and that longitudinal axis subregions are also associated with significant shared, hippocampus-general, genetic factors. Our study's findings suggest that genetic differences in hippocampal longitudinal axis structure can be detected in individual differences in gray matter volume in population-level research designs.

Hippocampal subfield volumes in mild cognitive impairment and alzheimer's disease: a systematic review and meta-analysis

The hippocampus is a complex structure that consists of several subfields with distinct and specialized functions. Although numerous studies have been performed to explore hippocampal atrophy at the sub-regional level in mild cognitive impairment (MCI) and Alzheimer's disease (AD), the results have been inconsistent especially for whether and which subfields can be served as the most potential biomarkers in MCI and AD. Herein, we used a meta-analytic approach to synthesize the extant literatures on hippocampal subfields in MCI and AD through PubMed, Web of Science, and Embase (PROSPERO CRD42021257586). As a result, a total of twenty studies using Freesurfer 5 and Freesurfer 6 were included in this investigation. These studies revealed that at the sub-regional level, hippocampal subfield volume reductions in MCI and AD were not restricted to specific subfields, and subiculum and presubiculum had the largest z-scores across most comparisons. However, none of the subfield performed much better in discriminating MCI and HC, AD and MCI, AD and HC as compared to whole hippocampus volume. These results suggested that we should explore the changes in the hippocampal subfields in subtypes of MCI or even at an earlier stage, that is subjective cognitive impairment.

Shared Genetic Architecture between Parkinson's Disease and Brain Structural Phenotypes

BACKGROUND

Patients with Parkinson's disease (PD) have consistently demonstrated brain structure abnormalities, indicating the presence of shared etiological and pathological processes between PD and brain structures; however, the genetic relationship remains poorly understood.

OBJECTIVE

The aim of this study was to investigate the extent of shared genetic architecture between PD and brain structural phenotypes (BSPs) and to identify shared genomic loci.

METHODS

We used the summary statistics from genome-wide association studies to conduct MiXeR and conditional/conjunctional false discovery rate analyses to investigate the shared genetic signatures between PD and BSPs. Subsequent expression quantitative trait loci mapping in the human brain and enrichment analyses were also performed.

RESULTS

MiXeR analysis identified genetic overlap between PD and various BSPs, including total cortical surface area, average cortical thickness, and specific brain volumetric structures. Further analysis using conditional false discovery rate (FDR) identified 21 novel PD risk loci on associations with BSPs at conditional FDR < 0.01, and the conjunctional FDR analysis demonstrated that PD shared several genomic loci with certain BSPs at conjunctional FDR < 0.05. Among the shared loci, 16 credible mapped genes showed high expression in the brain tissues and were primarily associated with immune function-related biological processes.

CONCLUSIONS

We confirmed the polygenic overlap with mixed directions of allelic effects between PD and BSPs and identified multiple shared genomic loci and risk genes, which are likely related to immune-related biological processes. These findings provide insight into the complex genetic architecture associated with PD. © 2023 International Parkinson and Movement Disorder Society.

Association between NTRK2 Polymorphisms, Hippocampal Volumes and Treatment Resistance in Major Depressive Disorder

Despite the increasing availability of antidepressant drugs, a high rate of patients with major depression (MDD) does not respond to pharmacological treatments. Brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signaling is thought to influence antidepressant efficacy and hippocampal volumes, robust predictors of treatment resistance. We therefore hypothesized the possible role of BDNF and neurotrophic receptor tyrosine kinase 2 (NTRK2)-related polymorphisms in affecting both hippocampal volumes and treatment resistance in MDD. A total of 121 MDD inpatients underwent 3T structural MRI scanning and blood sampling to obtain genotype information. General linear models and binary logistic regressions were employed to test the effect of genetic variations related to BDNF and NTRK2 on bilateral hippocampal volumes and treatment resistance, respectively. Finally, the possible mediating role of hippocampal volumes on the relationship between genetic markers and treatment response was investigated. A significant association between one NTRK2 polymorphism with hippocampal volumes and antidepressant response was found, with significant indirect effects. Our results highlight a possible mechanistic explanation of antidepressant action, possibly contributing to the understanding of MDD pathophysiology.

SLC4A10 mutation causes a neurological disorder associated with impaired GABAergic transmission

SLC4A10 is a plasma-membrane bound transporter that utilizes the Na+ gradient to drive cellular HCO3- uptake, thus mediating acid extrusion. In the mammalian brain, SLC4A10 is expressed in principal neurons and interneurons, as well as in epithelial cells of the choroid plexus, the organ regulating the production of CSF. Using next generation sequencing on samples from five unrelated families encompassing nine affected individuals, we show that biallelic SLC4A10 loss-of-function variants cause a clinically recognizable neurodevelopmental disorder in humans. The cardinal clinical features of the condition include hypotonia in infancy, delayed psychomotor development across all domains and intellectual impairment. Affected individuals commonly display traits associated with autistic spectrum disorder including anxiety, hyperactivity and stereotyped movements. In two cases isolated episodes of seizures were reported in the first few years of life, and a further affected child displayed bitemporal epileptogenic discharges on EEG without overt clinical seizures. While occipitofrontal circumference was reported to be normal at birth, progressive postnatal microcephaly evolved in 7 out of 10 affected individuals. Neuroradiological features included a relative preservation of brain volume compared to occipitofrontal circumference, characteristic narrow sometimes 'slit-like' lateral ventricles and corpus callosum abnormalities. Slc4a10 -/- mice, deficient for SLC4A10, also display small lateral brain ventricles and mild behavioural abnormalities including delayed habituation and alterations in the two-object novel object recognition task. Collapsed brain ventricles in both Slc4a10-/- mice and affected individuals suggest an important role of SLC4A10 in the production of the CSF. However, it is notable that despite diverse roles of the CSF in the developing and adult brain, the cortex of Slc4a10-/- mice appears grossly intact. Co-staining with synaptic markers revealed that in neurons, SLC4A10 localizes to inhibitory, but not excitatory, presynapses. These findings are supported by our functional studies, which show the release of the inhibitory neurotransmitter GABA is compromised in Slc4a10-/- mice, while the release of the excitatory neurotransmitter glutamate is preserved. Manipulation of intracellular pH partially rescues GABA release. Together our studies define a novel neurodevelopmental disorder associated with biallelic pathogenic variants in SLC4A10 and highlight the importance of further analyses of the consequences of SLC4A10 loss-of-function for brain development, synaptic transmission and network properties.

Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

METHODS

A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

RESULTS

Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

Piecing it together: atrophy profiles of hippocampal subfields relate to cognitive impairment along the Alzheimer's disease spectrum

Introduction

People with Alzheimer's disease (AD) experience more rapid declines in their ability to form hippocampal-dependent memories than cognitively normal healthy adults. Degeneration of the whole hippocampal formation has previously been found to covary with declines in learning and memory, but the associations between subfield-specific hippocampal neurodegeneration and cognitive impairments are not well characterized in AD. To improve prognostic procedures, it is critical to establish in which hippocampal subfields atrophy relates to domain-specific cognitive declines among people along the AD spectrum. In this study, we examine high-resolution structural magnetic resonance imaging (MRI) of the medial temporal lobe and extensive neuropsychological data from 29 amyloid-positive people on the AD spectrum and 17 demographically-matched amyloid-negative healthy controls.

Methods

Participants completed a battery of neuropsychological exams including select tests of immediate recollection, delayed recollection, and general cognitive status (i.e., performance on the Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). Hippocampal subfield volumes (CA1, CA2, CA3, dentate gyrus, and subiculum) were measured using a dedicated MRI slab sequence targeting the medial temporal lobe and used to compute distance metrics to quantify AD spectrum-specific atrophic patterns and their impact on cognitive outcomes.

Results

Our results replicate prior studies showing that CA1, dentate gyrus, and subiculum hippocampal subfield volumes were significantly reduced in AD spectrum participants compared to amyloid-negative controls, whereas CA2 and CA3 did not exhibit such patterns of atrophy. Moreover, degeneration of the subiculum along the AD spectrum was linked to a significant decline in general cognitive status measured by the MMSE, while degeneration scores of the CA1 and dentate gyrus were more widely associated with declines on the MMSE and tests of learning and memory.

Discussion

These findings provide evidence that subfield-specific patterns of hippocampal degeneration, in combination with cognitive assessments, may constitute a sensitive prognostic approach and could be used to better track disease trajectories among individuals on the AD spectrum.

A fast non-parametric test of association for multiple traits

The increasing availability of multidimensional phenotypic data in large cohorts of genotyped individuals requires efficient methods to identify genetic effects on multiple traits. Permutational multivariate analysis of variance (PERMANOVA) offers a powerful non-parametric approach. However, it relies on permutations to assess significance, which hinders the analysis of large datasets. Here, we derive the limiting null distribution of the PERMANOVA test statistic, providing a framework for the fast computation of asymptotic p values. Our asymptotic test presents controlled type I error and high power, often outperforming parametric approaches. We illustrate its applicability in the context of QTL mapping and GWAS.

The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation

BACKGROUND

The correlation between human gut microbiota and psychiatric diseases has long been recognized. Based on the heritability of the microbiome, genome-wide association studies on human genome and gut microbiome (mbGWAS) have revealed important host-microbiome interactions. However, establishing causal relationships between specific gut microbiome features and psychological conditions remains challenging due to insufficient sample sizes of previous studies of mbGWAS.

METHODS

Cross-cohort meta-analysis (via METAL) and multi-trait analysis (via MTAG) were used to enhance the statistical power of mbGWAS for identifying genetic variants and genes. Using two large mbGWAS studies (7,738 and 5,959 participants respectively) and12 disease-specific studies from the Psychiatric Genomics Consortium (PGC), we performed bidirectional two-sample mendelian randomization (MR) analyses between microbial features and psychiatric diseases (up to 500,199 individuals). Additionally, we conducted downstream gene- and gene-set-based analyses to investigate the shared biology linking gut microbiota and psychiatric diseases.

RESULTS

METAL and MTAG conducted in mbGWAS could boost power for gene prioritization and MR analysis. Increases in the number of lead SNPs and mapped genes were witnessed in 13/15 species and 5/10 genera after using METAL, and MTAG analysis gained an increase in sample size equivalent to expanding the original samples from 7% to 63%. Following METAL use, we identified a positive association between Bacteroides faecis and ADHD (OR, 1.09; 95 %CI, 1.02-1.16; P = 0.008). Bacteroides eggerthii and Bacteroides thetaiotaomicron were observed to be positively associated with PTSD (OR, 1.11; 95 %CI, 1.03-1.20; P = 0.007; OR, 1.11; 95 %CI, 1.01-1.23; P = 0.03). These findings remained stable across statistical models and sensitivity analyses. No genetic liabilities to psychiatric diseases may alter the abundance of gut microorganisms.Using biological annotation, we identified that those genes contributing to microbiomes (e.g., GRIN2A and RBFOX1) are expressed and enriched in human brain tissues.

CONCLUSIONS

Our statistical genetics strategy helps to enhance the power of mbGWAS, and our genetic findings offer new insights into biological pleiotropy and causal relationship between microbiota and psychiatric diseases.

Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy

Personality and cognitive function are heritable mental traits whose genetic foundations may be distributed across interconnected brain functions. Previous studies have typically treated these complex mental traits as distinct constructs. We applied the 'pleiotropy-informed' multivariate omnibus statistical test to genome-wide association studies of 35 measures of neuroticism and cognitive function from the UK Biobank (n = 336,993). We identified 431 significantly associated genetic loci with evidence of abundant shared genetic associations, across personality and cognitive function domains. Functional characterization implicated genes with significant tissue-specific expression in all tested brain tissues and brain-specific gene sets. We conditioned independent genome-wide association studies of the Big 5 personality traits and cognitive function on our multivariate findings, boosting genetic discovery in other personality traits and improving polygenic prediction. These findings advance our understanding of the polygenic architecture of these complex mental traits, indicating a prominence of pleiotropic genetic effects across higher order domains of mental function such as personality and cognitive function.

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits

BACKGROUND

The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders.

METHODS

We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits.

RESULTS

We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3).

CONCLUSIONS

Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

Smaller cornu ammonis (CA3) as a potential risk factor for suicidal behavior in mood disorders

Mood disorders and suicidal behavior have moderate heritability and familial transmission, and are associated with smaller hippocampal volumes. However, it is unclear whether hippocampal alterations reflect heritable risk or epigenetic effects of childhood adversity, compensatory mechanisms, illness-related changes, or treatment effects. We sought to separate the relationships of hippocampal substructure volumes to mood disorder, suicidal behavior, and risk and resilience to both by examining high familial risk individuals (HR) who have passed the age of greatest risk for psychopathology onset. Structural brain imaging and hippocampal substructure segmentation quantified Cornu Ammonis (CA1-4), dentate gyrus, and subiculum gray matter volumes in healthy volunteers (HV, N = 25) and three groups with one or more relatives reporting early-onset mood disorder and suicide attempt: 1. Unaffected HR (N = 20); 2. HR with lifetime mood disorder and no suicide attempt (HR-MOOD, N = 25); and 3. HR with lifetime mood disorder and a previous suicide attempt (HR-MOOD + SA, N = 18). Findings were tested in an independent cohort not selected for family history (HV, N = 47; MOOD, N = 44; and MOOD + SA, N = 21). Lower CA3 volume was found in HR (vs. HV), consistent with the direction of previously published findings in MOOD+SA (vs. HV and MOOD), suggesting the finding reflects a familial biological risk marker, not illness or treatment-related sequelae, of suicidal behavior and mood disorder. Familial suicide risk may be mediated in part by smaller CA3 volume. The structure may serve as a risk indicator and therapeutic target for suicide prevention strategies in high-risk families.

Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes

The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10^-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases

BACKGROUND

The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed.

METHODS

Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases.

RESULTS

We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10^-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases.

DISCUSSION

Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

Polygenic Risk for Schizophrenia, Major Depression, and Post-traumatic Stress Disorder and Hippocampal Subregion Volumes in Middle Childhood

Studies demonstrate that individuals with diagnoses for Major Depressive Disorder (MDD), Post-traumatic Stress Disorder (PTSD), and Schizophrenia (SCZ) may exhibit smaller hippocampal gray matter relative to otherwise healthy controls, although the effect sizes vary in each disorder. Existing work suggests that hippocampal abnormalities in each disorder may be attributable to genetic liability and/or environmental variables. The following study uses baseline data from the Adolescent Brain and Cognitive Development[Formula: see text] Study (ABCD Study[Formula: see text]) to address three open questions regarding the relationship between genetic risk for each disorder and hippocampal volume reductions: (a) whether polygenic risk scores (PGRS) for MDD, PTSD, and SCZ are related to hippocampal volume; (b) whether PGRS for MDD, PTSD, and SCZ are differentially related to specific hippocampal subregions along the longitudinal axis; and (c) whether the association between PGRS for MDD, PTSD, and SCZ and hippocampal volume is moderated by sex and/or environmental adversity. In short, we did not find associations between PGRS for MDD, PTSD, and SCZ to be significantly related to any hippocampal subregion volumes. Furthermore, neither sex nor enviornmental adversity significantly moderated these associations. Our study provides an important null finding on the relationship genetic risk for MDD, PTSD, and SCZ to measures of hippocampal volume.

Functional activity level reported by an informant is an early predictor of Alzheimer's disease

BACKGROUND

Loss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer's disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these changes are given medical attention. In the present study, we ask if such subtle changes should be given weight as an early predictor of a future AD diagnosis.

METHODS

Longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to define a group of adults with a mild cognitive impairment (MCI) diagnosis remaining stable across several visits (sMCI, n=360; 55-91 years at baseline), and a group of adults who over time converted from having an MCI diagnosis to an AD diagnosis (cAD, n=320; 55-88 years at baseline). Eleven features were used as input in a Random Forest (RF) binary classifier (sMCI vs. cAD) model. This model was tested on an unseen holdout part of the dataset, and further explored by three different permutation-driven importance estimates and a comprehensive post hoc machine learning exploration.

RESULTS

The results consistently showed that measures of daily life functioning, verbal memory function, and a volume measure of hippocampus were the most important predictors of conversion from an MCI to an AD diagnosis. Results from the RF classification model showed a prediction accuracy of around 70% in the test set. Importantly, the post hoc analyses showed that even subtle changes in everyday functioning noticed by a close informant put MCI patients at increased risk for being on a path toward the major cognitive impairment of an AD diagnosis.

CONCLUSION

The results showed that even subtle changes in everyday functioning should be noticed when reported by relatives in a clinical evaluation of patients with MCI. Information of these changes should also be included in future longitudinal studies to investigate different pathways from normal cognitive aging to the cognitive decline characterizing different stages of AD and other neurodegenerative disorders.

Genetic architecture of the white matter connectome of the human brain

White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the left-hemisphere language network. Polygenic scores for psychiatric, neurological, and behavioral traits also showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to variation in the structural connectome of the human brain.

Deciphering the Effect of Different Genetic Variants on Hippocampal Subfield Volumes in the General Population

The aim of this study was to disentangle the effects of various genetic factors on hippocampal subfield volumes using three different approaches: a biologically driven candidate gene approach, a hypothesis-free GWAS approach, and a polygenic approach, where AD risk alleles are combined with a polygenic risk score (PRS). The impact of these genetic factors was investigated in a large dementia-free general population cohort from the Study of Health in Pomerania (SHIP, n = 1806). Analyses were performed using linear regression models adjusted for biological and environmental risk factors. Hippocampus subfield volume alterations were found for APOE ε4, BDNF Val, and 5-HTTLPR L allele carriers. In addition, we were able to replicate GWAS findings, especially for rs17178139 (MSRB3), rs1861979 (DPP4), rs7873551 (ASTN2), and rs572246240 (MAST4). Interaction analyses between the significant SNPs as well as the PRS for AD revealed no significant results. Our results confirm that hippocampal volume reductions are influenced by genetic variation, and that different variants reveal different association patterns that can be linked to biological processes in neurodegeneration. Thus, this study underlines the importance of specific genetic analyses in the quest for acquiring deeper insights into the biology of hippocampal volume loss, memory impairment, depression, and neurodegenerative diseases.

Categorical and Dimensional Deficits in Hippocampal Subfields Among Schizophrenia, Obsessive-Compulsive Disorder, Bipolar Disorder, and Major Depressive Disorder

BACKGROUND

The hippocampus is a core region of interest for all major mental disorders, and its subfields implement distinctive functions. It is unclear whether the mental disorders exhibit common patterns of hippocampal impairments, and we lack knowledge on whether and how hippocampal subfields represent deficit spectra across mental disorders.

METHODS

Using brain images of 1123 individuals scanned on a single magnetic resonance imaging scanner, we examined the commonality, specificity, and symptom associations of the volume of hippocampal subfields across patients with schizophrenia, patients with obsessive-compulsive disorder, patients with bipolar disorder, patients with major depressive disorder, and healthy control subjects. We further performed a transdiagnostic analysis of the individual variability of the volume of hippocampal subfields to reflect cross-disease gradients in the hippocampus.

RESULTS

We found common and disease-specific abnormalities in a few hippocampal fields and identified 2 reliable transdiagnostic factors in the hippocampal subfields, each reflecting a spectrum of mental disorders. The plane spanned by the 2 most reliable factors provided a clearer view of hippocampal volume abnormality spectra among the major mental disorders. In addition, functional and genetic enrichment analyses supported the different roles of the 2 hippocampal factors in mental disorders.

CONCLUSIONS

The volume of hippocampal subfields reflected some commonality and specificity among the 3 major mental disorders. We propose a new pathophysiological dimensional view of the hippocampus, reflecting at least 2 spectra of mental disorders, suggesting multivariate links among the diseases. This work highlights the value of the complementary categorical and dimensional views of the hippocampal deficits in mental disorders.

Heritability of hippocampal functional and microstructural organisation

The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation may be explained by experience-driven factors. Last, we demonstrate that structure and function couple along an inherited macroscale organisation, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal of the structure and function within the hippocampal organisation.

Comprehensive analysis of shared genetic loci between hippocampal volume and schizophrenia

Schizophrenia and hippocampal volume exhibit a genetic correlation, but the underlying genetic mechanisms remain unclear. Here, we investigated the shared genetic variants in schizophrenia and hippocampal volume using the largest genome-wide association studies (GWASs) data. We identified three genetic loci associated with both schizophrenia and hippocampal volume. Functional annotation analysis suggested that shared genetic variants play a major role via the regulatory effect on gene expression. Expression pattern analyses showed that candidate genes have a spatiotemporal and cell-specific expression pattern across human brain development. These findings provided deeper insights into the genetic mechanisms underlying hippocampus and schizophrenia risk.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Associations between brain imaging and polygenic scores of mental health and educational attainment in children aged 9-11

Psychiatric disorders are highly heritable and polygenic, and many have their peak onset in late childhood and adolescence, a period of tremendous changes. Although the neurodevelopmental antecedents of mental illness are widely acknowledged, research in youth population cohorts is still scarce, preventing our progress towards the early characterization of these disorders. We included 7,124 children (9-11 years old) from the Adolescent Brain and Cognitive Development Study to map the associations of structural and diffusion brain imaging with common genetic variants and polygenic scores for psychiatric disorders and educational attainment. We used principal component analysis to derive imaging components, and calculated their heritability. We then assessed the relationship of imaging components with genetic and clinical psychiatric risk with univariate models and Canonical correlation analysis (CCA). Most imaging components had moderate heritability. Univariate models showed limited evidence and small associations of polygenic scores with brain structure at this age. CCA revealed two significant modes of covariation. The first mode linked higher polygenic scores for educational attainment with less externalizing problems and larger surface area. The second mode related higher polygenic scores for schizophrenia, bipolar disorder, and autism spectrum disorder to higher global cortical thickness, smaller white matter volumes of the fornix and cingulum, larger medial occipital surface area and smaller surface area of lateral and medial temporal regions. While cross-validation suggested limited generalizability, our results highlight the potential of multivariate models to better understand the transdiagnostic and distributed relationships between mental health and brain structure in late childhood.

Investigating the Genetic Characteristics of Hippocampal Volume and Plasma β-Amyloid in a Chinese Community-Dwelling Population

BACKGROUND AND OBJECTIVES

The genetic characteristics and correlations of hippocampal volume (HV) and plasma β-amyloid (Aβ), probable endophenotypes for dementia, remain to be explored in a Chinese community cohort. Using whole-exome sequencing (WES) and single nucleotide polymorphism (SNP) array genotyping, we sought to identify rare and common variants and genes influencing these 2 endophenotypes and calculate their heritability and genetic correlation.

METHODS

Association analyses with both WES and SNP array genotyping data were performed for HV and plasma Aβ with mixed-effect linear regression model adjusted for sex, age, and total intracranial volume or APOE ε4 while considering familial relatedness. We also performed gene-level analysis for common and gene burden analysis for rare variants. Heritability and genetic correlation were examined further.

RESULTS

A total of 1,261 participants from a Chinese community cohort were included and we identified 1 gene, PTPRT, for HV, with the top significant SNPs by whole genome-wide association study (GWAS). rs6030076 (p = 5.48 × 10-8, β = -0.092, SE 0.017) from WES and rs6030088 (p = 8.24 × 10-9, β = -105.22, SE 18.09) from SNP array data were both located in this gene. Gene burden analysis based on rare mutations detected 6 genes to be significantly associated with Aβ. The SNP-based heritability was 0.43 ± 0.13 for HV and 0.2-0.3 for plasma Aβ. The SNP-based genetic correlation between HV and plasma Aβ was negative.

DISCUSSION

In this study, we identified several SNPs and 1 gene, PTPRT, which were not reported in previous GWAS, associated with HV. The heritability and the genetic correlation gave an overview of HV and plasma Aβ. Our findings provide insights into the mechanisms behind the individual variances in these endophenotypes.

Genetic Specificity of Hippocampal Subfield Volumes, Relative to Hippocampal Formation, Identified in 2148 Young Adult Twins and Siblings

The hippocampus is a complex brain structure with key roles in cognitive and emotional processing and with subregion abnormalities associated with a range of disorders and psychopathologies. Here we combine data from two large independent young adult twin/sibling cohorts to obtain the most accurate estimates to date of genetic covariation between hippocampal subfield volumes and the hippocampus as a single volume. The combined sample included 2148 individuals, comprising 1073 individuals from 627 families (mean age = 22.3 years) from the Queensland Twin IMaging (QTIM) Study, and 1075 individuals from 454 families (mean age = 28.8 years) from the Human Connectome Project (HCP). Hippocampal subfields were segmented using FreeSurfer version 6.0 (CA4 and dentate gyrus were phenotypically and genetically indistinguishable and were summed to a single volume). Multivariate twin modeling was conducted in OpenMx to decompose variance into genetic and environmental sources. Bivariate analyses of hippocampal formation and each subfield volume showed that 10%-72% of subfield genetic variance was independent of the hippocampal formation, with greatest specificity found for the smaller volumes; for example, CA2/3 with 42% of genetic variance being independent of the hippocampus; fissure (63%); fimbria (72%); hippocampus-amygdala transition area (41%); parasubiculum (62%). In terms of genetic influence, whole hippocampal volume is a good proxy for the largest hippocampal subfields, but a poor substitute for the smaller subfields. Additive genetic sources accounted for 49%-77% of total variance for each of the subfields in the combined sample multivariate analysis. In addition, the multivariate analyses were sufficiently powered to identify common environmental influences (replicated in QTIM and HCP for the molecular layer and CA4/dentate gyrus, and accounting for 7%-16% of total variance for 8 of 10 subfields in the combined sample). This provides the clearest indication yet from a twin study that factors such as home environment may influence hippocampal volumes (albeit, with caveats).

Interpersonal Family Dynamics Relate to Hippocampal CA Subfield Structure

Social environments that are extremely enriched or adverse can influence hippocampal volume. Though most individuals experience social environments that fall somewhere in between these extremes, substantially less is known about the influence of normative variation in social environments on hippocampal structure. Here, we examined whether hippocampal volume tracks normative variation in interpersonal family dynamics in 7- to 12-year-olds and adults recruited from the general population. We focused on interpersonal family dynamics as a prominent feature of one's social world. Given evidence that CA1 and CA2 play a key role in tracking social information, we related individual hippocampal subfield volumes to interpersonal family dynamics. More positive perceptions of interpersonal family dynamics were associated with greater CA1 and CA2/3 volume regardless of age and controlling for socioeconomic status. These data suggest that CA subfields are sensitive to normative variation in social environments and identify interpersonal family dynamics as an impactful environmental feature.

Distributed genetic architecture across the hippocampal formation implies common neuropathology across brain disorders

Despite its major role in complex human functions across the lifespan, most notably navigation, learning and memory, much of the genetic architecture of the hippocampal formation is currently unexplored. Here, through multivariate genome-wide association analysis in volumetric data from 35,411 white British individuals, we reveal 177 unique genetic loci with distributed associations across the hippocampal formation. We identify genetic overlap with eight brain disorders with typical onset at different stages of life, where common genes suggest partly age- and disorder-independent mechanisms underlying hippocampal pathology.

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.

Gene Expression Profiles of the Aging Rat Hippocampus Imply Altered Immunoglobulin Dynamics

Aging is a process that leads to the deterioration in physiological functioning of the brain. Prior research has proposed that hippocampal aging is accompanied by genetic alterations in neural, synaptic, and immune functions. Nevertheless, interactome-based interrogations of gene alterations in hippocampal aging, remain scarce. Our study integrated gene expression profiles of the hippocampus from young and aged rats and functionally classified network-mapped genes based on their interactome. Hippocampal differentially expressed genes (DEGs) between young (5-8 months) and aged (21-26 months) male rats (Rattus norvegicus) were retrieved from five publicly available datasets (GSE14505, GSE20219, GSE14723, GSE14724, and GSE14725; 38 young and 29 aged samples). Encoded hippocampal proteins of age-related DEGs and their interactome were predicted. Clustered network DEGs were identified and the highest-ranked was functionally annotated. A single cluster of 19 age-related hippocampal DEGs was revealed, which was linked with immune response (biological process, P = 1.71E-17), immunoglobulin G binding (molecular function, P = 1.92E-08), and intrinsic component of plasma membrane (cellular component, P = 1.25E-06). Our findings revealed dysregulated hippocampal immunoglobulin dynamics in the aging rat brain. Whether a consequence of neurovascular perturbations and dysregulated blood-brain barrier permeability, the role of hippocampal immunoregulation in the pathobiology of aging warrants further investigation.

Long-Term Cannabis Use and Cognitive Reserves and Hippocampal Volume in Midlife

OBJECTIVE

Cannabis use is increasing among midlife and older adults. This study tested the hypotheses that long-term cannabis use is associated with cognitive deficits and smaller hippocampal volume in midlife, which is important because midlife cognitive deficits and smaller hippocampal volume are risk factors for dementia.

METHODS

Participants are members of a representative cohort of 1,037 individuals born in Dunedin, New Zealand, in 1972-1973 and followed to age 45, with 94% retention. Cannabis use and dependence were assessed at ages 18, 21, 26, 32, 38, and 45. IQ was assessed at ages 7, 9, 11, and 45. Specific neuropsychological functions and hippocampal volume were assessed at age 45.

RESULTS

Long-term cannabis users showed IQ decline from childhood to midlife (mean=-5.5 IQ points), poorer learning and processing speed relative to their childhood IQ, and informant-reported memory and attention problems. These deficits were specific to long-term cannabis users because they were either not present or were smaller among long-term tobacco users, long-term alcohol users, midlife recreational cannabis users, and cannabis quitters. Cognitive deficits among long-term cannabis users could not be explained by persistent tobacco, alcohol, or other illicit drug use, childhood socioeconomic status, low childhood self-control, or family history of substance dependence. Long-term cannabis users showed smaller hippocampal volume, but smaller hippocampal volume did not statistically mediate cannabis-related cognitive deficits.

CONCLUSIONS

Long-term cannabis users showed cognitive deficits and smaller hippocampal volume in midlife. Research is needed to ascertain whether long-term cannabis users show elevated rates of dementia in later life.

Volume deficits in hippocampal subfields in unaffected relatives of schizophrenia patients with high genetic loading but without any psychiatric symptoms

BACKGROUND

Hippocampal volume changes have been reported in schizophrenia patients and their relatives and are proposed to contribute to the pathophysiology of schizophrenia. However, volume changes in the total hippocampus have not been consistently reported in relatives. The hippocampus consists of multiple subregions, and based on previous inconsistent results, subtle changes in specific subregions may occur in relatives. Here, we examined the subregion volumes in unaffected, high-functioning relatives (URs) without any psychiatric symptoms with high genetic loading with at least one first-degree relative diagnosed with schizophrenia and at least one or more other affected first- to third-degree relatives.

METHODS

We acquired structural magnetic resonance imaging data from 50 URs, 101 first-episode psychosis (FEP) patients, and 101 healthy controls (HCs). The cornu ammonis (CA), dentate gyrus, and subiculum subfields were automatically segmented using FreeSurfer 7.1.0. Each subregion volume was compared across the groups.

RESULTS

Compared with the HCs, the URs had a significant volume reduction in the left anterior CA (p = 0.039, Cohen's d = 0.480). In addition, the URs had a significantly larger right posterior subiculum (p = 0.001, Cohen's d = 0.541) than the FEP.

CONCLUSIONS

The smaller left anterior CA in the URs may reflect their genetic vulnerability to schizophrenia and supports previous findings suggesting specific vulnerability in this region. The volume differences between the URs and FEP patients in the right posterior subiculum may suggest that a smaller volume in this region may reflect a risk for schizophrenia other than genetic vulnerability.

Lacking Social Support is Associated With Structural Divergences in Hippocampus-Default Network Co-Variation Patterns

Elaborate social interaction is a pivotal asset of the human species. The complexity of people’s social lives may constitute the dominating factor in the vibrancy of many individuals’ environment. The neural substrates linked to social cognition thus appear especially susceptible when people endure periods of social isolation: here, we zoom in on the systematic inter-relationships between two such neural substrates, the allocortical hippocampus (HC) and the neocortical default network (DN). Previous human social neuroscience studies have focused on the DN, while HC subfields have been studied in most detail in rodents and monkeys. To bring into contact these two separate research streams, we directly quantified how DN subregions are coherently co-expressed with specific HC subfields in the context of social isolation. A two-pronged decomposition of structural brain scans from ∼40 000 UK Biobank participants linked lack of social support to mostly lateral subregions in the DN patterns. This lateral DN association co-occurred with HC patterns that implicated especially subiculum, presubiculum, CA2, CA3 and dentate gyrus. Overall, the subregion divergences within spatially overlapping signatures of HC–DN co-variation followed a clear segregation into the left and right brain hemispheres. Separable regimes of structural HC–DN co-variation also showed distinct associations with the genetic predisposition for lacking social support at the population level.

Contribution of schizophrenia polygenic burden to longitudinal phenotypic variance in 22q11.2 deletion syndrome

While the recurrent 22q11.2 deletion is one of the strongest genetic risk factors for schizophrenia (SCZ), variability of its associated neuropsychiatric endophenotypes reflects its incomplete penetrance for psychosis development. To assess whether this phenotypic variability is linked to common variants associated with SCZ, we studied the association between SCZ polygenic risk score (PRS) and longitudinally acquired phenotypic information of the Swiss 22q11.2DS cohort (n = 97, 50% females, mean age 17.7 yr, mean visit interval 3.8 yr). The SCZ PRS with the best predictive performance was ascertained in the Estonian Biobank (n = 201,146) with LDpred. The infinitesimal SCZ PRS model showed the strongest capacity in discriminating SCZ cases from controls with one SD difference in SCZ PRS corresponding to an odds ratio (OR) of 1.73 (95% CI 1.57-1.90, P = 1.47 × 10^-29). In 22q11.2 patients, random-effects ordinal regression modelling using longitudinal data showed SCZ PRS to have the strongest effect on social anhedonia (OR = 2.09, P = 0.0002), and occupational functioning (OR = 1.82, P = 0.0003) within the negative symptoms course, and dysphoric mood (OR = 2.00, P = 0.002) and stress intolerance (OR = 1.76, P = 0.0002) within the general symptoms course. Genetic liability for SCZ was additionally associated with full scale cognitive decline (β = -0.25, P = 0.02) and with longitudinal volumetric reduction of the right and left hippocampi (β = -0.28, P = 0.005; β = -0.23, P = 0.02, respectively). Our results indicate that the polygenic contribution to SCZ acts upon the threshold-lowering first hit (i.e., the deletion). It modifies the endophenotypes of 22q11.2DS and augments the derailment of developmental trajectories of negative and general symptoms, cognition, and hippocampal volume.