Heritability of Hippocampal Formation Sub-region Volumes

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.

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).

Association Between Hippocampal Subfields and Clinical Symptoms of First-Episode and Drug Naive Schizophrenia Patients During 12 Weeks of Risperidone Treatment

Small hippocampal size may be implicated in the pathogenesis and psychopathology of schizophrenia (SCZ). However, does the volume of hippocampal subfields in SCZ patients affect response to antipsychotic treatment? In this study, we used risperidone to treat first-episode drug naïve (FEDN) SCZ patients for 12 weeks, and then explored the relationship between baseline hippocampal subfield volumes, as well as any changes in these hippocampal subfield volumes during treatment, and improvement in their psychopathological symptoms. By adopting a state-of the-art automated algorithm, the hippocampal subfields were segmented in 43 FEDN SCZ inpatients at baseline and after 12 weeks of risperidone monotherapy, as well as in 30 matched healthy controls. We adopted the Positive and Negative Syndrome Scale (PANSS) to assess psychopathological symptoms in patients at baseline and at post-treatment. Before treatment, SCZ patients had no significant differences in total or subfield hippocampal volumes compared with healthy volunteers. However, we found a significant correlation between a smaller left CA1 at baseline and a lower PANSS total score and general psychopathology sub-score at post-treatment (both p < 0.05). Furthermore, the left CA1 at baseline was significantly smaller in responders, who had >50% improvement in PANSS total score, than in non-responders (p < 0.05). Our results suggest that smaller left CA1 volume may be a predicator for improvement in psychotic symptoms of FEDN SCZ patients.

Genetic Influences on Hippocampal Subfields: An Emerging Area of Neuroscience Research

There is clear evidence that hippocampal subfield volumes have partly distinct genetic determinants associated with specific biological processes. The identification of genetic correlates of hippocampal subfield volumes may help to elucidate the mechanisms of neurologic diseases, as well as aging and neurodegenerative processes. However, despite the emerging interest in this area of research, the current knowledge of the genetic architecture of hippocampal subfields has not yet been consolidated. We aimed to provide a review of the current evidence from genetic studies of hippocampal subfields, highlighting current priorities and upcoming challenges. The limited number of studies investigating the influential genetic effects on hippocampal subfields, a lack of replicated results and longitudinal designs, and modest sample sizes combined with insufficient standardization of protocols are identified as the most pressing challenges in this emerging area of research.

Human Connectome Project: heritability of brain volumes in young healthy adults

Here we report on the heritability and Intraclass Correlation Coefficients (ICCs) of brain volumes in 1,103 young healthy adults with mean age 29.2 years. Among them are: 153 monozygotic (MZ) twin pairs and 86 dizygotic (DZ) twin pairs, 133 non-twin siblings of MZ twins, 76 non-twin siblings of DZ twins, 335 siblings, and 81 unrelated individuals. ICCs were calculated between pairs of the following genetic groups: (1) MZ twins; (2) DZ twins; (3) MZ twins-their singleton siblings; (4) DZ twins-their singleton siblings; (5) siblings (SB); and (6) unrelated individuals (NR). We studied 4 brain groups: global, lobar, subcortical, and cortical brain regions. For each of 4 brain groups we found the same order of ICCs ranging from the highest values for MZ twins, statistically significantly smaller for the DZ twins and 3 sibling groups, and practically zero for NR. The DZ twins and 3 sibling groups were not different. No hemispheric difference was found in any genetic group. Among brain groups, the highest heritability was for the global regions, followed by lobar and subcortical groups. Only the cortical brain group heritability was statistically lower than other brain groups. We found less genetic control on the left hemisphere than on the right but no significant difference between hemispheres, and no hemispheric lateralization of heritability for any of the brain groups. These findings document substantial and systematic heritability of global and regional brain volumes.

FreeSurfer ‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.

Volumetric GWAS of medial temporal lobe structures identifies an ERC1 locus using ADNI high-resolution T2-weighted MRI data

Medial temporal lobe (MTL) consists of hippocampal subfields and neighboring cortices. These heterogeneous structures are differentially involved in memory, cognitive and emotional functions, and present nonuniformly distributed atrophy contributing to cognitive disorders. This study aims to examine how genetics influences Alzheimer's disease (AD) pathogenesis via MTL substructures by analyzing high-resolution magnetic resonance imaging (MRI) data. We performed genome-wide association study to examine the associations between 565,373 single nucleotide polymorphisms (SNPs) and 14 MTL substructure volumes. A novel association with right Brodmann area 36 volume was discovered in an ERC1 SNP (i.e., rs2968869). Further analyses on larger samples found rs2968869 to be associated with gray matter density and glucose metabolism measures in the right hippocampus, and disease status. Tissue-specific transcriptomic analysis identified the minor allele of rs2968869 (rs2968869-C) to be associated with reduced ERC1 expression in the hippocampus. All the findings indicated a protective role of rs2968869-C in AD. We demonstrated the power of high-resolution MRI and the promise of fine-grained MTL substructures for revealing the genetic basis of AD biomarkers.

Heritability of Regional Brain Volumes in Large-Scale Neuroimaging and Genetic Studies

Brain genetics is an active research area. The degree to which genetic variants impact variations in brain structure and function remains largely unknown. We examined the heritability of regional brain volumes (P ~ 100) captured by single-nucleotide polymorphisms (SNPs) in UK Biobank (n ~ 9000). We found that regional brain volumes are highly heritable in this study population and common genetic variants can explain up to 80% of their variabilities (median heritability 34.8%). We observed omnigenic impact across the genome and examined the enrichment of SNPs in active chromatin regions. Principal components derived from regional volume data are also highly heritable, but the amount of variance in brain volume explained by the component did not seem to be related to its heritability. Heritability estimates vary substantially across large-scale functional networks, exhibit a symmetric pattern across left and right hemispheres, and are consistent in females and males (correlation = 0.638). We repeated the main analysis in Alzheimer's Disease Neuroimaging Initiative (n ~ 1100), Philadelphia Neurodevelopmental Cohort (n ~ 600), and Pediatric Imaging, Neurocognition, and Genetics (n ~ 500) datasets, which demonstrated that more stable estimates can be obtained from the UK Biobank.

Dentate gyrus volume deficit in schizophrenia

BACKGROUND

Schizophrenia is associated with robust hippocampal volume deficits but subregion volume deficits, their associations with cognition, and contributing genes remain to be determined.

METHODS

Hippocampal formation (HF) subregion volumes were obtained using FreeSurfer 6.0 from individuals with schizophrenia (n = 176, mean age ± s.d. = 39.0 ± 11.5, 132 males) and healthy volunteers (n = 173, mean age ± s.d. = 37.6 ± 11.3, 123 males) with similar mean age, gender, handedness, and race distributions. Relationships between the HF subregion volume with the largest between group difference, neuropsychological performance, and single-nucleotide polymorphisms were assessed.

RESULTS

This study found a significant group by region interaction on hippocampal subregion volumes. Compared to healthy volunteers, individuals with schizophrenia had significantly smaller dentate gyrus (DG) (Cohen's d = -0.57), Cornu Ammonis (CA) 4, molecular layer of the hippocampus, hippocampal tail, and CA 1 volumes, when statistically controlling for intracranial volume; DG (d = -0.43) and CA 4 volumes remained significantly smaller when statistically controlling for mean hippocampal volume. DG volume showed the largest between group difference and significant positive associations with visual memory and speed of processing in the overall sample. Genome-wide association analysis with DG volume as the quantitative phenotype identified rs56055643 (β = 10.8, p < 5 × 10-8, 95% CI 7.0-14.5) on chromosome 3 in high linkage disequilibrium with MOBP. Gene-based analyses identified associations between SLC25A38 and RPSA and DG volume.

CONCLUSIONS

This study suggests that DG dysfunction is fundamentally involved in schizophrenia pathophysiology, that it may contribute to cognitive abnormalities in schizophrenia, and that underlying biological mechanisms may involve contributions from MOBP, SLC25A38, and RPSA.

Shared genetic influences on adolescent body mass index and brain structure: A voxel-based morphometry study in twins

BACKGROUND

Previous research has demonstrated significant relationships between obesity and brain structure. Both phenotypes are heritable, but it is not known whether they are influenced by common genetic factors. We investigated the genetic etiology of the relationship between individual variability in brain morphology and BMIz using structural MRI in adolescent twins.

METHOD

The sample (n = 258) consisted of 54 monozygotic and 75 dizygotic twin pairs (mean(SD) age = 13.61(0.505), BMIz = 0.608(1.013). Brain structure (volume and density of gray and white matter) was assessed using VBM. Significant voxelwise heritability of brain structure was established using the Accelerated Permutation inference for ACE models (APACE) program, with structural heritability varying from 15 to 97%, depending on region. Bivariate heritability analyses were carried out comparing additive genetic and unique environment models with and without shared genetics on BMIz and the voxels showing significant heritability in the APACE analyses.

RESULTS

BMIz was positively related to gray matter volume in the brainstem and thalamus and negatively related to gray matter volume in the bilateral uncus and medial orbitofrontal cortex, gray matter density in the cerebellum, prefrontal lobe, temporal lobe, and limbic system, and white matter density in the brainstem. Bivariate heritability analyses showed that BMIz and brain structure share ∼1/3 of their genes and that ∼95% of the phenotypic correlation between BMIz and brain structure is due to shared additive genetic influences. These regions included areas related to decision-making, motivation, liking vs. wanting, taste, interoception, reward processing/learning, caloric evaluation, and inhibition.

CONCLUSION

These results suggested genetic factors are responsible for the relationship between BMIz and heritable BMIz related brain structure in areas related to eating behavior.

Genetic architecture of hippocampal subfields on standard resolution MRI: How the parts relate to the whole

The human hippocampus can be subdivided into subfields with unique functional properties and differential vulnerability to disease or neuropsychiatric conditions. Identifying genes that confer susceptibility to such processes is an important goal in developing treatments. Recent advances in automatic subfield segmentation from magnetic resonance images make it possible to use these measures as phenotypes in large-scale genome-wide association studies. Such analyses are likely to rely largely on standard resolution (~1 mm isotropic) T₁ -weighted images acquired on 3.0T scanners. Determining whether the genetic architecture of subfields can be detected from such images is therefore an important step. We used Freesurfer v6.0 to segment hippocampal subfields in two large twin studies, the Vietnam Era Twin Study of Aging and the Human Connectome Project. We estimated heritability of subfields and the genetic overlap with total hippocampal volume. Heritability was similar across samples, but little genetic variance remained after accounting for genetic influences on total hippocampal volume. Importantly, we examined genetic relationships between subfields to determine whether subfields can be grouped based on a smaller number of underlying, genetically independent factors. We identified three genetic factors in both samples, but the high degree of cross loadings precluded formation of genetically distinct groupings of subfields. These results confirm the reliability of Freesurfer v6.0 generated subfields across samples for phenotypic analyses. However, the current results suggest that it will be difficult for large-scale genetic analyses to identify subfield-specific genes that are distinct from both total hippocampal volume and other subfields using segmentations generated from standard resolution T₁ -weighted images.

Hippocampal subregion abnormalities in schizophrenia: A systematic review of structural and physiological imaging studies

Aim

The hippocampus is considered a key region in schizophrenia pathophysiology, but the nature of hippocampal subregion abnormalities and how they contribute to disease expression remain to be fully determined. This study reviews findings from schizophrenia hippocampal subregion volumetric and physiological imaging studies published within the last decade.

Methods

The PubMed database was searched for publications on hippocampal subregion volume and physiology abnormalities in schizophrenia and their findings were reviewed.

Results

The main replicated findings include smaller CA1 volumes and CA1 hyperactivation in schizophrenia, which may be predictive of conversion in individuals at clinical high risk of psychosis, smaller CA1 and CA4/DG volumes in first‐episode schizophrenia, and more widespread smaller hippocampal subregion volumes with longer duration of illness. Several studies have reported relationships between hippocampal subregion volumes and declarative memory or symptom severity.

Conclusions

Together these studies provide support for hippocampal formation circuitry models of schizophrenia. These initial findings must be taken with caution as the scientific community is actively working on hippocampal subregion method improvement and validation. Further improvements in our understanding of the nature of hippocampal formation subregion involvement in schizophrenia will require the collection of structural and physiological imaging data at submillimeter voxel resolution, standardization and agreement of atlases, adequate control for possible confounding factors, and multi‐method validation of findings. Despite the need for cautionary interpretation of the initial findings, we believe that improved localization of hippocampal subregion abnormalities in schizophrenia holds promise for the identification of disease contributing mechanisms.

The hippocampus is considered a key region in schizophrenia pathophysiology but the nature of hippocampal subregion abnormalities and how they contribute to disease expression remains to be fully determined. This study reviews findings from schizophrenia hippocampal subregion volumetric and physiological imaging studies published within the last decade.

Hippocampal Subregions Across the Psychosis Spectrum

INTRODUCTION

Converging evidence suggests that hippocampal subregions subserve different functions, and are differentially affected by psychosis illness progression. Despite this fact, studies have not often studied subregions cross-sectionally across the psychosis spectrum. Furthermore, little is known about associations between subregion volumes and hippocampus-mediated cognition.

METHODS

A total of 222 participants (61 ultra high risk [UHR], 91 schizophrenia [SCZ], and 70 healthy volunteers) underwent a 3T MRI scan, as well as structured clinical interviews and a cognitive battery. Hippocampal subfield analysis was conducted with Freesurfer. We compared subregion volumes across groups, controlling for age, gender, and intracranial volume. We also examined associations in the UHR and SCZ groups between hippocampal subregion volumes and verbal learning, visual learning, and working memory.

RESULTS

We found a dose-dependent relationship such that the SCZ group showed significantly greater subfield volume reductions than the UHR group, which in turn showed significantly greater subfield volume reductions than the healthy volunteer group. We also found associations between subregion volume and cognitive performance in the visual memory, verbal memory, and working memory domains.

DISCUSSION

Our study examined hippocampal subregion volumes cross-sectionally in a large sample across the psychosis spectrum, as well as links with hippocampus-mediated cognitive function. Our findings suggest that hippocampal abnormalities emerge before first psychosis episode onset, and may be etiologically informative.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.