Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Statistical Genetic Approaches to Investigate Genotype-by-Environment Interaction: Review and Novel Extension of Models

Statistical genetic models of genotype-by-environment (G×E) interaction can be divided into two general classes, one on G×E interaction in response to dichotomous environments (e.g., sex, disease-affection status, or presence/absence of an exposure) and the other in response to continuous environments (e.g., physical activity, nutritional measurements, or continuous socioeconomic measures). Here we develop a novel model to jointly account for dichotomous and continuous environments. We develop the model in terms of a joint genotype-by-sex (for the dichotomous environment) and genotype-by-social determinants of health (SDoH; for the continuous environment). Using this model, we show how a depression variable, as measured by the Beck Depression Inventory-II survey instrument, is not only underlain by genetic effects (as has been reported elsewhere) but is also significantly determined by joint G×Sex and G×SDoH interaction effects. This model has numerous applications leading to potentially transformative research on the genetic and environmental determinants underlying complex diseases.

Multi-omics and pathway analyses of genome-wide associations implicate regulation and immunity in verbal declarative memory performance

BACKGROUND

Uncovering the functional relevance underlying verbal declarative memory (VDM) genome-wide association study (GWAS) results may facilitate the development of interventions to reduce age-related memory decline and dementia.

METHODS

We performed multi-omics and pathway enrichment analyses of paragraph (PAR-dr) and word list (WL-dr) delayed recall GWAS from 29,076 older non-demented individuals of European descent. We assessed the relationship between single-variant associations and expression quantitative trait loci (eQTLs) in 44 tissues and methylation quantitative trait loci (meQTLs) in the hippocampus. We determined the relationship between gene associations and transcript levels in 53 tissues, annotation as immune genes, and regulation by transcription factors (TFs) and microRNAs. To identify significant pathways, gene set enrichment was tested in each cohort and meta-analyzed across cohorts. Analyses of differential expression in brain tissues were conducted for pathway component genes.

RESULTS

The single-variant associations of VDM showed significant linkage disequilibrium (LD) with eQTLs across all tissues and meQTLs within the hippocampus. Stronger WL-dr gene associations correlated with reduced expression in four brain tissues, including the hippocampus. More robust PAR-dr and/or WL-dr gene associations were intricately linked with immunity and were influenced by 31 TFs and 2 microRNAs. Six pathways, including type I diabetes, exhibited significant associations with both PAR-dr and WL-dr. These pathways included fifteen MHC genes intricately linked to VDM performance, showing diverse expression patterns based on cognitive status in brain tissues.

CONCLUSIONS

VDM genetic associations influence expression regulation via eQTLs and meQTLs. The involvement of TFs, microRNAs, MHC genes, and immune-related pathways contributes to VDM performance in older individuals.

3DCNN predicting brain age using diffusion tensor imaging

Neuroimaging-based brain age prediction using deep learning is gaining popularity. However, few studies have attempted to leverage diffusion tensor imaging (DTI) to predict brain age. In this study, we proposed a 3D convolutional neural network model (3DCNN) and trained it on fractional anisotropy (FA) data from six publicly available datasets (n = 2406, age = 17-60) to estimate brain age. Implementing a two-loop nested cross-validation scheme with a tenfold cross-validation procedure, we achieved a robust prediction performance of a mean absolute error (MAE) of 2.785 and a correlation coefficient of 0.932. We also employed Grad-Cam++ to visualize the salient features of the proposed model. We identified a few highly salient fiber tracts, including the genu of corpus callosum and the left cerebellar peduncle, among others that play a pivotal role in our model. In sum, our model reliably predicted brain age and provided novel insight into age-related changes in brains' axonal structure.

Meta-analysis of age-related cognitive decline reveals a novel locus for the attention domain and implicates a COVID-19-related gene for global cognitive function

INTRODUCTION

Cognitive abilities have substantial heritability throughout life, as shown by twin- and population-based studies. However, there is limited understanding of the genetic factors related to cognitive decline in aging across neurocognitive domains.

METHODS

We conducted a meta-analysis on 3045 individuals aged ≥65, derived from three population-based cohorts, to identify genetic variants associated with the decline of five neurocognitive domains (attention, memory, executive function, language, visuospatial function) and global cognitive decline. We also conducted gene-based and functional bioinformatics analyses.

RESULTS

Apolipoprotein E (APOE)4 was significantly associated with decline of memory (p = 5.58E-09) and global cognitive function (p = 1.84E-08). We identified a novel association with attention decline on chromosome 9, rs6559700 (p = 2.69E-08), near RASEF. Gene-based analysis also identified a novel gene, TMPRSS11D, involved in the activation of SARS-CoV-2, to be associated with the decline in global cognitive function (p = 4.28E-07).

DISCUSSION

Domain-specific genetic studies can aid in the identification of novel genes and pathways associated with decline across neurocognitive domains.

HIGHLIGHTS

rs6559700 was associated with decline of attention. APOE4 was associated with decline of memory and global cognitive decline. TMPRSS11D, a gene involved in the activation of SARS-CoV-2, was implicated in global cognitive decline. Cognitive domain abilities had both unique and shared molecular pathways across the domains.

Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms

White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.

Effects of polygenic risk of schizophrenia on interhemispheric callosal white matter integrity and frontotemporal functional connectivity in first-episode schizophrenia

BACKGROUND

Schizophrenia is a severely debilitating psychiatric disorder with high heritability and polygenic architecture. A higher polygenic risk score for schizophrenia (SzPRS) has been associated with smaller gray matter volume, lower activation, and decreased functional connectivity (FC). However, the effect of polygenic inheritance on the brain white matter microstructure has only been sparsely reported.

METHODS

Eighty-four patients with first-episode schizophrenia (FES) patients and ninety-three healthy controls (HC) with genetics, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI) data were included in our study. We investigated impaired white matter integrity as measured by fractional anisotropy (FA) in the FES group, further examined the effect of SzPRS on white matter FA and FC in the regions connected by SzPRS-related white matter tracts.

RESULTS

Decreased FA was observed in FES in many commonly identified regions. Among these regions, we observed that in the FES group, but not the HC group, SzPRS was negatively associated with the mean FA in the genu and body of corpus callosum, right anterior corona radiata, and right superior corona radiata. Higher SzPRS was also associated with lower FCs between the left inferior frontal gyrus (IFG)-left inferior temporal gyrus (ITG), right IFG-left ITG, right IFG-left middle frontal gyrus (MFG), and right IFG-right MFG in the FES group.

CONCLUSION

Higher polygenic risks are linked with disrupted white matter integrity and FC in patients with schizophrenia. These correlations are strongly driven by the interhemispheric callosal fibers and the connections between frontotemporal regions.

The Genetic contribution to solving the cocktail-party problem

Communicating in everyday situations requires solving the cocktail-party problem, or segregating the acoustic mixture into its constituent sounds and attending to those of most interest. Humans show dramatic variation in this ability, leading some to experience real-world problems irrespective of whether they meet criteria for clinical hearing loss. Here, we estimated the genetic contribution to cocktail-party listening by measuring speech-reception thresholds (SRTs) in 425 people from large families and ranging in age from 18 to 91 years. Roughly half the variance of SRTs was explained by genes (h ² = 0.567). The genetic correlation between SRTs and hearing thresholds (HTs) was medium (ρ _G = 0.392), suggesting that the genetic factors influencing cocktail-party listening were partially distinct from those influencing sound sensitivity. Aging and socioeconomic status also strongly influenced SRTs. These findings may represent a first step toward identifying genes for "hidden hearing loss," or hearing problems in people with normal HTs.

Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD

The neurodevelopmental model of schizophrenia is supported by multi-level impairments shared among schizophrenia and neurodevelopmental disorders. Despite schizophrenia and typical neurodevelopmental disorders, i.e., autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), as disorders of brain dysconnectivity, no study has ever elucidated whether whole-brain white matter (WM) tracts integrity alterations overlap or diverge between these three disorders. Moreover, whether the linked dimensions of cognition and brain metrics per the Research Domain Criteria framework cut across diagnostic boundaries remains unknown. We aimed to map deviations from normative ranges of whole-brain major WM tracts for individual patients to investigate the similarity and differences among schizophrenia (281 patients subgrouped into the first-episode, subchronic and chronic phases), ASD (175 patients), and ADHD (279 patients). Sex-specific WM tract normative development was modeled from diffusion spectrum imaging of 626 typically developing controls (5-40 years). There were three significant findings. First, the patterns of deviation and idiosyncrasy of WM tracts were similar between schizophrenia and ADHD alongside ASD, particularly at the earlier stages of schizophrenia relative to chronic stages. Second, using the WM deviation patterns as features, schizophrenia cannot be separated from neurodevelopmental disorders in the unsupervised machine learning algorithm. Lastly, the canonical correlation analysis showed schizophrenia, ADHD, and ASD shared linked cognitive dimensions driven by WM deviations. Together, our results provide new insights into the neurodevelopmental facet of schizophrenia and its brain basis. Individual's WM deviations may contribute to diverse arrays of cognitive function along a continuum with phenotypic expressions from typical neurodevelopmental disorders to schizophrenia.

Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes

BACKGROUND

Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration.

METHODS

Using large population-based brain imaging datasets across the lifespan (N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in young (18-35 years), middle (35-65 years), and older (65+ years) age, and their genetic correlation across age groups; 2) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; and 3) explore their association with neurological phenotypes.

RESULTS

Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, 10 loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age.

CONCLUSIONS

Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.

The Role of OXT, OXTR, AVP, and AVPR1a Gene Expression in the Course of Schizophrenia

Schizophrenia is a serious and chronic mental illness, the symptoms of which usually appear for the first time in late adolescence or early adulthood. To date, much research has been conducted on the etiology of schizophrenia; however, it is still not fully understood. Oxytocin and vasopressin as neuromodulators that regulate social and emotional behavior are promising candidates for determining the vulnerability to schizophrenia. The aim of this study was to evaluate the expression of OXT, OXTR, AVP, and AVPR1a genes at the mRNA and protein levels in patients with schizophrenia. Due to the neurodegenerative nature of schizophrenia, the study group was divided into two subgroups, namely, G1 with a diagnosis that was made between 10 and 15 years after the onset of the illness, and G2 with a diagnosis made up to two years after the onset of the illness. Moreover, the relationship between the examined genes and the severity of schizophrenia symptoms, assessed using PANSS (Positive and Negative Syndrome Scale) and CDSS scales (Clinical Depression Scale for Schizophrenia) was evaluated. The analysis of the expression of the studied genes at the mRNA and protein levels showed statistically significant differences in the expression of all the investigated genes. OXT and AVPR1a gene expression at both the mRNA and protein levels were significantly lower in the schizophrenia group, and OXTR and AVP gene expression at both the mRNA and protein levels was higher in the schizophrenia subjects than in the controls. Furthermore, a significant correlation of OXT gene expression at the mRNA and protein levels with the severity of depressive symptoms in schizophrenia as assessed by CDSS was found.

Comparing empirical kinship derived heritability for imaging genetics traits in the UK biobank and human connectome project

Imaging genetics analyses use neuroimaging traits as intermediate phenotypes to infer the degree of genetic contribution to brain structure and function in health and/or illness. Coefficients of relatedness (CR) summarize the degree of genetic similarity among subjects and are used to estimate the heritability – the proportion of phenotypic variance explained by genetic factors. The CR can be inferred directly from genome-wide genotype data to explain the degree of shared variation in common genetic polymorphisms (SNP-heritability) among related or unrelated subjects. We developed a central processing and graphics processing unit (CPU and GPU) accelerated Fast and Powerful Heritability Inference (FPHI) approach that linearizes likelihood calculations to overcome the ~N^2–3 computational effort dependency on sample size of classical likelihood approaches. We calculated for 60 regional and 1.3 × 10⁵ voxel-wise traits in N = 1,206 twin and sibling participants from the Human Connectome Project (HCP) (550 M/656 F, age = 28.8 ± 3.7 years) and N = 37,432 (17,531 M/19,901 F; age = 63.7 ± 7.5 years) participants from the UK Biobank (UKBB). The FPHI estimates were in excellent agreement with heritability values calculated using Genome-wide Complex Trait Analysis software (r = 0.96 and 0.98 in HCP and UKBB sample) while significantly reducing computational (10^2–4 times). The regional and voxel-wise traits heritability estimates for the HCP and UKBB were likewise in excellent agreement (r = 0.63–0.76, p < 10⁻¹⁰). In summary, the hardware-accelerated FPHI made it practical to calculate heritability values for voxel-wise neuroimaging traits, even in very large samples such as the UKBB. The patterns of additive genetic variance in neuroimaging traits measured in a large sample of related and unrelated individuals showed excellent agreement regardless of the estimation method. The code and instruction to execute these analyses are available at www.solar-eclipse-genetics.org.

Neurological Soft Signs (NSS) in Census-Based, Decade-Adjusted Healthy Adults, 20 to >70 Years of Age

Neurological soft signs (NSS) represent minor neurological features and have been widely studied in psychiatric disease. The assessment is easily performed. Quantity and quality may provide useful information concerning the disease course. Mostly, NSS scores differ significantly between patients and controls. However, literature does not give reference values. In this pilot study, we recruited 120 healthy women and men to build a cross-sectional, census-based sample of healthy individuals, aged 20 to >70 years, subdivided in 10-year blocks for a close approach to the human lifeline. Testing for NSS and neurocognitive functioning was performed following the exclusion of mental and severe physical illness. NSS scores increased significantly between ages 50+ and 60+, which was primarily accountable to motor signs. Gender and cognitive functioning were not related to changes of scores. Although the number of individuals is small, study results may lay a foundation for further validation of NSS in healthy individuals.

Genetic influences on externalizing psychopathology overlap with cognitive functioning and show developmental variation

BACKGROUND

Questions remain regarding whether genetic influences on early life psychopathology overlap with cognition and show developmental variation.

METHODS

Using data from 9,421 individuals aged 8-21 from the Philadelphia Neurodevelopmental Cohort, factors of psychopathology were generated using a bifactor model of item-level data from a psychiatric interview. Five orthogonal factors were generated: anxious-misery (mood and anxiety), externalizing (attention deficit hyperactivity and conduct disorder), fear (phobias), psychosis-spectrum, and a general factor. Genetic analyses were conducted on a subsample of 4,662 individuals of European American ancestry. A genetic relatedness matrix was used to estimate heritability of these factors, and genetic correlations with executive function, episodic memory, complex reasoning, social cognition, motor speed, and general cognitive ability. Gene × Age analyses determined whether genetic influences on these factors show developmental variation.

RESULTS

Externalizing was heritable (h2 = 0.46, p = 1 × 10-6), but not anxious-misery (h2 = 0.09, p = 0.183), fear (h2 = 0.04, p = 0.337), psychosis-spectrum (h2 = 0.00, p = 0.494), or general psychopathology (h2 = 0.21, p = 0.040). Externalizing showed genetic overlap with face memory (ρg = -0.412, p = 0.004), verbal reasoning (ρg = -0.485, p = 0.001), spatial reasoning (ρg = -0.426, p = 0.010), motor speed (ρg = 0.659, p = 1x10-4), verbal knowledge (ρg = -0.314, p = 0.002), and general cognitive ability (g)(ρg = -0.394, p = 0.002). Gene × Age analyses revealed decreasing genetic variance (γg = -0.146, p = 0.004) and increasing environmental variance (γe = 0.059, p = 0.009) on externalizing.

CONCLUSIONS

Cognitive impairment may be a useful endophenotype of externalizing psychopathology and, therefore, help elucidate its pathophysiological underpinnings. Decreasing genetic variance suggests that gene discovery efforts may be more fruitful in children than adolescents or young adults.

A White Matter Connection of Schizophrenia and Alzheimer's Disease

Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.

Genetic influence on cognitive development between childhood and adulthood

Successful cognitive development between childhood and adulthood has important consequences for future mental and physical wellbeing, as well as occupational and financial success. Therefore, delineating the genetic influences underlying changes in cognitive abilities during this developmental period will provide important insights into the biological mechanisms that govern both typical and atypical maturation. Using data from the Philadelphia Neurodevelopmental Cohort (PNC), a large population-based sample of individuals aged 8 to 21 years old (n = 6634), we used an empirical relatedness matrix to establish the heritability of general and specific cognitive functions and determine if genetic factors influence cognitive maturation (i.e., Gene × Age interactions) between childhood and early adulthood. We found that neurocognitive measures across childhood and early adulthood were significantly heritable. Moreover, genetic variance on general cognitive ability, or g, increased significantly between childhood and early adulthood. Finally, we did not find evidence for decay in genetic correlation on neurocognition throughout childhood and adulthood, suggesting that the same genetic factors underlie cognition at different ages throughout this developmental period. Establishing significant Gene × Age interactions in neurocognitive functions across childhood and early adulthood is a necessary first step in identifying genes that influence cognitive development, rather than genes that influence cognition per se. Moreover, since aberrant cognitive development confers risk for several psychiatric disorders, further examination of these Gene × Age interactions may provide important insights into their etiology.

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

Synergistic information in a dynamical model implemented on the human structural connectome reveals spatially distinct associations with age

We implement the dynamical Ising model on the large-scale architecture of white matter connections of healthy subjects in the age range 4-85 years, and analyze the dynamics in terms of the synergy, a quantity measuring the extent to which the joint state of pairs of variables is projected onto the dynamics of a target one. We find that the amount of synergy in explaining the dynamics of the hubs of the structural connectivity (in terms of degree strength) peaks before the critical temperature, and can thus be considered as a precursor of a critical transition. Conversely, the greatest amount of synergy goes into explaining the dynamics of more central nodes. We also find that the aging of structural connectivity is associated with significant changes in the simulated dynamics: There are brain regions whose synergy decreases with age, in particular the frontal pole, the subcallosal area, and the supplementary motor area; these areas could then be more likely to show a decline in terms of the capability to perform higher order computation (if structural connectivity was the sole variable). On the other hand, several regions in the temporal cortex show a positive correlation with age in the first 30 years of life, that is, during brain maturation.

Computerized Cognitive Rehabilitation Training for Ugandan Seniors Living with HIV: A Validation Study

The feasibility, acceptability and preliminary efficacy of computerized cognitive rehabilitation therapy (CCRT) for mitigating neurocognitive decline was evaluated in African adults ≥50 years old. Eighty-one Ugandans with (n = 40) and without (n = 41) chronic human immunodeficiency viruses (HIV) were allocated CCRT—i.e., 20–45-min cognitive training sessions with culturally adapted video games delivered via Captain’s Log Software, or standard of care (SOC). Pre and post (i.e., 8-weeks later) intervention performance based neurocognitive tests, quality of life (QOL) and frailty related phenotype (FRP) were determined in all respondents. Multivariable linear regression estimated CCRT- vs. SOC-related differences (β) in neurocognitive batteries, QOL and FRP. Effect sizes (ES) for estimated β were calculated. CCRT protocol was completed by 92.8% of persons allocated to it. Regardless of HIV status, CCRT was associated with higher performance in learning tests than SOC—interference list (β = 1.00, 95%CI: (0.02, 1.98); ES = 0.43) and delayed recall (β = 1.04, 95%CI: (0.06, 2.02); ES = 0.47). CCRT effect on verbal fluency was clinically important (ES = 0.38), but statistical significance was not reached (β = 1.25, 95%CI: (−0.09, 2.58)). Among HIV-positive adults, clinically important post-CCRT improvements were noted for immediate recall (ES = 0.69), working memory (ES = 0.51), verbal fluency (ES = 0.51), and timed gait (ES = −0.44) tasks. Among HIV-negative adults, CCRT resulted in moderate post-intervention improvement in learning tests (ES = 0.45) and large decline in FRP (ES = −0.71), without a positive effect on simple attention and visuomotor coordination tasks. CCRT intervention is feasible among older Ugandan adults with potential benefit for learning and verbal fluency tests regardless of HIV status and lowering FRP in HIV-negative older adults.

Cingulum and abnormal psychological stress response in schizophrenia

Stress is implicated in many aspects of schizophrenia, including heightened distress intolerance. We examined how affect and microstructure of major brain tracts involved in regulating affect may contribute to distress intolerance in schizophrenia. Patients with schizophrenia spectrum disorders (n = 78) and community controls (n = 95) completed diffusion weighted imaging and performed psychological stress tasks. Subjective affect was collected pre and post stressors. Individuals who did not persist during one or both stress tasks were considered distress intolerant (DI), and otherwise distress tolerant (DT). Fractional anisotropy (FA) of the dorsal cingulum showed a significant diagnosis x DT/DI phenotype interaction (p = 0.003). Post-hoc tests showed dorsal cingulum FA was significantly lower in DI patients compared with DI controls (p < 0.001), but not different between DT groups (p = 0.27). Regarding affect responses to stress, irritability showed the largest stress-related change (p < 0.001), but irritability changes were significantly reduced in DI patients compared to DI controls (p = 0.006). The relationship between irritability change and performance errors also differed among patients (ρ = -0.29, p = 0.011) and controls (ρ = 0.21, p = 0.042). Further modeling highlighted the explanatory power of dorsal cingulum for predicting DI even after performance and irritability were taken into account. Distress intolerance during psychological stress exposure is related to microstructural properties of the dorsal cingulum, a key structure for cognitive control and emotion regulation. In schizophrenia, the affective response to psychological stressors is abnormal, and distress intolerant patients had significantly reduced dorsal cingulum FA compared to distress intolerant controls. The findings provide new insight regarding distress intolerance in schizophrenia.

Functional network connectivity impairments and core cognitive deficits in schizophrenia

Cognitive deficits contribute to functional disability in patients with schizophrenia and may be related to altered functional networks that serve cognition. We evaluated the integrity of major functional networks and assessed their role in supporting two cognitive functions affected in schizophrenia: processing speed (PS) and working memory (WM). Resting-state functional magnetic resonance imaging (rsfMRI) data, N = 261 patients and 327 controls, were aggregated from three independent cohorts and evaluated using Enhancing NeuroImaging Genetics through Meta Analysis rsfMRI analysis pipeline. Meta- and mega-analyses were used to evaluate patient-control differences in functional connectivity (FC) measures. Canonical correlation analysis was used to study the association between cognitive deficits and FC measures. Patients showed consistent patterns of cognitive and resting-state FC (rsFC) deficits across three cohorts. Patient-control differences in rsFC calculated using seed-based and dual-regression approaches were consistent (Cohen's d: 0.31 ± 0.09 and 0.29 ± 0.08, p < 10^-4 ). RsFC measures explained 12-17% of the individual variations in PS and WM in the full sample and in patients and controls separately, with the strongest correlations found in salience, auditory, somatosensory, and default-mode networks. The pattern of association between rsFC (within-network) and PS (r = .45, p = .07) and WM (r = .36, p = .16), and rsFC (between-network) and PS (r = .52, p = 8.4 × 10^-3 ) and WM (r = .47, p = .02), derived from multiple networks was related to effect size of patient-control differences in the functional networks. No association was detected between rsFC and current medication dose or psychosis ratings. Patients demonstrated significant reduction in several FC networks that may partially underlie some of the core neurocognitive deficits in schizophrenia. The strength of connectivity-cognition relationships in different networks was strongly associated with network's vulnerability to schizophrenia.

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.

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r ∼0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web-based calculator (www.solar-eclipse-genetics.org/HCP).

Comparison of heritability estimates on resting state fMRI connectivity phenotypes using the ENIGMA analysis pipeline

We measured and compared heritability estimates for measures of functional brain connectivity extracted using the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) rsfMRI analysis pipeline in two cohorts: the genetics of brain structure (GOBS) cohort and the HCP (the Human Connectome Project) cohort. These two cohorts were assessed using conventional (GOBS) and advanced (HCP) rsfMRI protocols, offering a test case for harmonization of rsfMRI phenotypes, and to determine measures that show consistent heritability for in-depth genome-wide analysis. The GOBS cohort consisted of 334 Mexican-American individuals (124M/210F, average age = 47.9 ± 13.2 years) from 29 extended pedigrees (average family size = 9 people; range 5-32). The GOBS rsfMRI data was collected using a 7.5-min acquisition sequence (spatial resolution = 1.72 × 1.72 × 3 mm³ ). The HCP cohort consisted of 518 twins and family members (240M/278F; average age = 28.7 ± 3.7 years). rsfMRI data was collected using 28.8-min sequence (spatial resolution = 2 × 2 × 2 mm³ ). We used the single-modality ENIGMA rsfMRI preprocessing pipeline to estimate heritability values for measures from eight major functional networks, using (1) seed-based connectivity and (2) dual regression approaches. We observed significant heritability (h² = 0.2-0.4, p < .05) for functional connections from seven networks across both cohorts, with a significant positive correlation between heritability estimates across two cohorts. The similarity in heritability estimates for resting state connectivity measurements suggests that the additive genetic contribution to functional connectivity is robustly detectable across populations and imaging acquisition parameters. The overarching genetic influence, and means to consistently detect it, provides an opportunity to define a common genetic search space for future gene discovery studies.

Miniature pig model of human adolescent brain white matter development

BACKGROUND

Neuroscience research in brain development and disorders can benefit from an in vivo animal model that portrays normal white matter (WM) development trajectories and has a sufficiently large cerebrum for imaging with human MRI scanners and protocols.

NEW METHOD

Twelve three-month-old Sinclair™ miniature pigs (Sus scrofa domestica) were longitudinally evaluated during adolescent development using advanced diffusion weighted imaging (DWI) focused on cerebral WM. Animals had three MRI scans every 23.95 ± 3.73 days using a 3-T scanner. The DWI imaging protocol closely modeled advanced human structural protocols and consisted of fifteen b-shells (b = 0-3500 s/mm2) with 32-directions/shell. DWI data were analyzed using diffusion kurtosis and bi-exponential modeling that provided measurements that included fractional anisotropy (FA), radial kurtosis, kurtosis anisotropy (KA), axial kurtosis, tortuosity, and permeability-diffusivity index (PDI).

RESULTS

Significant longitudinal effects of brain development were observed for whole-brain average FA, KA, and PDI (all p < 0.001). There were expected regional differences in trends, with corpus callosum fibers showing the highest rate of change.

COMPARISON WITH EXISTING METHOD(S)

Pigs have a large, gyrencephalic brain that can be studied using clinical MRI scanners/protocols. Pigs are less complex than non-human primates thus satisfying the "replacement" principle of animal research.

CONCLUSIONS

Longitudinal effects were observed for whole-brain and regional diffusion measurements. The changes in diffusion measurements were interepreted as evidence for ongoing myelination and maturation of cerebral WM. Corpus callosum and superficial cortical WM showed the expected higher rates of change, mirroring results in humans.

Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies

A novel mega-analytical approach that reduced methodological variance was evaluated using a multisite diffusion tensor imaging (DTI) fractional anisotropy (FA) data by comparing white matter integrity in people with schizophrenia to controls. Methodological variance was reduced through regression of variance captured from quality assurance (QA) and by using Marchenko-Pastur Principal Component Analysis (MP-PCA) denoising. N = 192 (119 patients/73 controls) data sets were collected at three sites equipped with 3T MRI systems: GE MR750, GE HDx, and Siemens Trio. DTI protocol included five b = 0 and 60 diffusion-sensitized gradient directions (b = 1,000 s/mm2 ). In-house DTI QA protocol data was acquired weekly using a uniform phantom; factor analysis was used to distil into two orthogonal QA factors related to: SNR and FA. They were used as site-specific covariates to perform mega-analytic data aggregation. The effect size of patient-control differences was compared to these reported by the enhancing neuro imaging genetics meta-analysis (ENIGMA) consortium before and after regressing QA variance. Impact of MP-PCA filtering was evaluated likewise. QA-factors explained ∼3-4% variance in the whole-brain average FA values per site. Regression of QA factors improved the effect size of schizophrenia on whole brain average FA values-from Cohen's d = .53 to .57-and improved the agreement between the regional pattern of FA differences observed in this study versus ENIGMA from r = .54 to .70. Application of MP-PCA-denoising further improved the agreement to r = .81. Regression of methodological variances captured by routine QA and advanced denoising that led to a better agreement with a large mega-analytic study.

Shared Genetic Factors Influence Head Motion During MRI and Body Mass Index

Head movements are typically viewed as a nuisance to functional magnetic resonance imaging (fMRI) analysis, and are particularly problematic for resting state fMRI. However, there is growing evidence that head motion is a behavioral trait with neural and genetic underpinnings. Using data from a large randomly ascertained extended pedigree sample of Mexican Americans (n = 689), we modeled the genetic structure of head motion during resting state fMRI and its relation to 48 other demographic and behavioral phenotypes. A replication analysis was performed using data from the Human Connectome Project, which uses an extended twin design (n = 864). In both samples, head motion was significantly heritable (h2 = 0.313 and 0.427, respectively), and phenotypically correlated with numerous traits. The most strongly replicated relationship was between head motion and body mass index, which showed evidence of shared genetic influences in both data sets. These results highlight the need to view head motion in fMRI as a complex neurobehavioral trait correlated with a number of other demographic and behavioral phenotypes. Given this, when examining individual differences in functional connectivity, the confounding of head motion with other traits of interest needs to be taken into consideration alongside the critical important of addressing head motion artifacts.

White matter deficits in schizophrenia are global and don't progress with age

INTRODUCTION

Diffusion tensor imaging has revealed differences in all examined white matter tracts in schizophrenia, with a range of explanations for why this may be. The distribution and timing of differences may help explain their origin; however, results are usually dependent on the analytical method. We therefore sought to examine the extent of differences and their relationship with age using two different methods.

METHODS

A combined voxel-based whole-brain study and a tract-based spatial-statistics study of 104 patients with schizophrenia and 200 matched healthy controls, aged between 17 and 63 years.

RESULTS

Fractional anisotropy was reduced throughout the brain in both analyses. The relationship of fractional anisotropy with age differed between patients and controls, with controls showing the gentle fractional anisotropy decline widely noted but patients showing an essentially flat relationship: younger patients had lower fractional anisotropy than controls, but the difference disappeared with age. Mean diffusivity was widely increased in patients.

CONCLUSION

Reduction in fractional anisotropy and increase in mean diffusivity would be consistent with global disruption in myelination; the relationship with age would suggest this is present already at the onset of their illness, but does not progress.

Association of White Matter With Core Cognitive Deficits in Patients With Schizophrenia

IMPORTANCE

Efforts to remediate the multiple cognitive function impairments in schizophrenia should consider white matter as one of the underlying neural mechanisms.

OBJECTIVE

To determine whether altered structural brain connectivity is responsible for 2 of the core cognitive deficits in schizophrenia- reduced information processing speed and impaired working memory.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study design took place in outpatient clinics from August 1, 2004, to August 31, 2015. Participants included 166 patients with schizophrenia and 213 healthy control individuals. These participants were from 3 independent cohorts, each of which had its own healthy control group. No participant had current or past neurological conditions or major medical conditions. Patients were diagnosed with either schizophrenia or schizoaffective disorder as defined by the DSM-IV. Controls had no Axis I psychiatric disorder.

MAIN OUTCOMES AND MEASURES

Mediation analyses and structural equation modeling were used to analyze the associations among processing speed, working memory, and white matter microstructures. Whole-brain and regional diffusion tensor imaging fractional anisotropy were used to measure white matter microstructures.

RESULTS

Of the study participants, the 166 patients with schizophrenia had a mean (SD) age of 38.2 (13.3) years and the 213 healthy controls had a mean (SD) age of 39.2 (14.0) years. There were significantly more male patients than controls in each of the 3 cohorts (117 [70%] vs 91 [43%]), but there were no significant differences in sex composition among the 3 cohorts. Patients had significantly reduced processing speed (Cohen d = 1.24; P = 6.91 × 10-30) and working memory deficits (Cohen d = 0.83; P = 1.10 × 10-14) as well as a significant whole-brain fractional anisotropy deficit (Cohen d = 0.63; P = 2.20 × 10-9). In schizophrenia, working memory deficit was mostly accounted for by processing speed deficit, but this deficit remained when accounting for working memory (Cohen d = 0.89; P = 2.21 × 10-17). Mediation analyses showed a significant association pathway from fractional anisotropy to processing speed to working memory (P = 5.01 × 10-7). The strength of this brain-to-cognition pathway in different white matter tracts was strongly associated with the severity of schizophrenia-associated fractional anisotropy deficits in the corresponding white matter tracts as determined by a meta-analysis (r = 0.85-0.94; all P < .001). The same pattern was observed in patients and controls either jointly or independently.

CONCLUSIONS AND RELEVANCE

Study findings suggest that (1) processing speed contributes to the association between white matter microstructure and working memory in schizophrenia and (2) white matter impairment in schizophrenia is regional tract-specific, particularly in tracts normally supporting processing speed performance.

Enhancing the Informativeness and Replicability of Imaging Genomics Studies

Imaging genomics is a new field of investigation that seeks to gain insights into the impact of human genetic variation on the structure, chemistry, and function of neural systems in health and disease. Because publications in this field have increased over the past decade, increasing concerns have been raised about false-positive results entering the literature. Here, we provide an overview of the field of imaging genomic and genetic approaches and discuss factors related to research design and analysis that can enhance the informativeness and replicability of these studies. We conclude that imaging genetic studies can provide important insights into the role of human genetic variation on neural systems and circuits, both in the context of normal quantitative variation and in relation to neuropsychiatric disease. We also argue that demonstrating genetic association to imaging-derived traits is subject to the same constraints as any other genetic study, including stringent type I error control. Adequately powered studies are necessary; however, there are currently limited data available to allow precise estimates of effect sizes for candidate gene studies. Independent replication is necessary before a result can be considered definitive, and for studies with small sample sizes it is necessary before publication. Increased transparency of methods and enhanced data sharing will further enhance replicability.

The Processing-Speed Impairment in Psychosis Is More Than Just Accelerated Aging

Processing speed is impaired in patients with psychosis, and deteriorates as a function of normal aging. These observations, in combination with other lines of research, suggest that psychosis may be a syndrome of accelerated aging. But do patients with psychosis perform poorly on tasks of processing speed for the same reasons as older adults? Fifty-one patients with psychotic illnesses and 90 controls with similar mean IQ (aged 19-69 years, all African American) completed a computerized processing-speed task, reminiscent of the classic digit-symbol coding task. The data were analyzed using the drift-diffusion model (DDM), and Bayesian inference was used to determine whether psychosis and aging had similar or divergent effects on the DDM parameters. Psychosis and aging were both associated with poor performance, but had divergent effects on the DDM parameters. Patients had lower information-processing efficiency ("drift rate") and longer nondecision time than controls, and psychosis per se did not influence response caution. By contrast, the primary effect of aging was to increase response caution, and had inconsistent effects on drift rate and nondecision time across patients and controls. The results reveal that psychosis and aging influenced performance in different ways, suggesting that the processing-speed impairment in psychosis is more than just accelerated aging. This study also demonstrates the potential utility of computational models and Bayesian inference for finely mapping the contributions of cognitive functions on simple neurocognitive tests.

Epigenetic Age Acceleration Assessed with Human White-Matter Images

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρ_pheno = -0.119, p = 0.028), with evidence of shared genetic (ρ_gene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging.

Potassium channel gene associations with joint processing speed and white matter impairments in schizophrenia

Patients with schizophrenia show decreased processing speed on neuropsychological testing and decreased white matter integrity as measured by diffusion tensor imaging, two traits shown to be both heritable and genetically associated indicating that there may be genes that influence both traits as well as schizophrenia disease risk. The potassium channel gene family is a reasonable candidate to harbor such a gene given the prominent role potassium channels play in the central nervous system in signal transduction, particularly in myelinated axons. We genotyped members of the large potassium channel gene family focusing on putatively functional single nucleotide polymorphisms (SNPs) in a population of 363 controls, 194 patients with schizophrenia spectrum disorder (SSD) and 28 patients with affective disorders with psychotic features who completed imaging and neuropsychological testing. We then performed three association analyses using three phenotypes - processing speed, whole-brain white matter fractional anisotropy (FA) and schizophrenia spectrum diagnosis. We extracted SNPs showing an association at a nominal P value of <0.05 with all three phenotypes in the expected direction: decreased processing speed, decreased FA and increased risk of SSD. A single SNP, rs8234, in the 3' untranslated region of voltage-gated potassium channel subfamily Q member 1 (KCNQ1) was identified. Rs8234 has been shown to affect KCNQ1 expression levels, and KCNQ1 levels have been shown to affect neuronal action potentials. This exploratory analysis provides preliminary data suggesting that KCNQ1 may contribute to the shared risk for diminished processing speed, diminished white mater integrity and increased risk of schizophrenia.

Heritability of white matter microstructure in late middle age: A twin study of tract-based fractional anisotropy and absolute diffusivity indices

There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Using an atlas-based registration approach to delineate individual white matter tracts, we investigated mean DTI-based indices within the corpus callosum, 12 bilateral tracts and all these regions of interest combined. All four diffusivity indices had high heritability at the global level (72%-80%). The magnitude of genetic effects in individual tracts varied from 0% to 82% for FA, 0% to 81% for MD, 8% to 77% for AD, and 0% to 80% for RD with most of the tracts showing significant heritability estimates. Despite the narrow age range of this community-based sample, age was correlated with all four diffusivity indices at the global level. In sum, all diffusion indices proved to have substantial heritability for most of the tracts and the heritability estimates were similar in magnitude for different diffusivity measures. Future studies could aim to discover the particular set of genes that underlie the significant heritability of white matter microstructure. Hum Brain Mapp 38:2026-2036, 2017. © 2017 Wiley Periodicals, Inc.

Genetic architecture of age-related cognitive decline in African Americans

OBJECTIVE

To identify genetic risk factors associated with susceptibility to age-related cognitive decline in African Americans (AAs).

METHODS

We performed a genome-wide association study (GWAS) and an admixture-mapping scan in 3,964 older AAs from 5 longitudinal cohorts; for each participant, we calculated a slope of an individual's global cognitive change from neuropsychological evaluations. We also performed a pathway-based analysis of the age-related cognitive decline GWAS.

RESULTS

We found no evidence to support the existence of a genomic region which has a strongly different contribution to age-related cognitive decline in African and European genomes. Known Alzheimer disease (AD) susceptibility variants in the ABCA7 and MS4A loci do influence this trait in AAs. Of interest, our pathway-based analyses returned statistically significant results highlighting a shared risk from lipid/metabolism and protein tyrosine signaling pathways between cognitive decline and AD, but the role of inflammatory pathways is polarized, being limited to AD susceptibility.

CONCLUSIONS

The genetic architecture of aging-related cognitive in AA individuals is largely similar to that of individuals of European descent. In both populations, we note a surprising lack of enrichment for immune pathways in the genetic risk for cognitive decline, despite strong enrichment of these pathways among genetic risk factors for AD.

Diffusion-weighted imaging uncovers likely sources of processing-speed deficits in schizophrenia

Schizophrenia, a devastating psychiatric illness with onset in the late teens to early 20s, is thought to involve disrupted brain connectivity. Functional and structural disconnections of cortical networks may underlie various cognitive deficits, including a substantial reduction in the speed of information processing in schizophrenia patients compared with controls. Myelinated white matter supports the speed of electrical signal transmission in the brain. To examine possible neuroanatomical sources of cognitive deficits, we used a comprehensive diffusion-weighted imaging (DWI) protocol and characterized the white matter diffusion signals using diffusion kurtosis imaging (DKI) and permeability-diffusivity imaging (PDI) in patients (n = 74), their nonill siblings (n = 41), and healthy controls (n = 113). Diffusion parameters that showed significant patient-control differences also explained the patient-control differences in processing speed. This association was also found for the nonill siblings of the patients. The association was specific to processing-speed abnormality but not specific to working memory abnormality or psychiatric symptoms. Our findings show that advanced diffusion MRI in white matter may capture microstructural connectivity patterns and mechanisms that govern the association between a core neurocognitive measure-processing speed-and neurobiological deficits in schizophrenia that are detectable with in vivo brain scans. These non-Gaussian diffusion white matter metrics are promising surrogate imaging markers for modeling cognitive deficits and perhaps, guiding treatment development in schizophrenia.

Heterochronicity of white matter development and aging explains regional patient control differences in schizophrenia

BACKGROUND

Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging.

METHODS

Three cohorts of schizophrenia patients (total n = 177) and controls (total n = 249; age = 18-61 years) were ascertained with three 3T Siemens MRI scanners. Whole-brain and regional FA values were extracted using ENIGMA-DTI protocols. Statistics were evaluated using mega- and meta-analyses to detect effects of diagnosis and age-by-diagnosis interactions.

RESULTS

In mega-analysis of whole-brain averaged FA, schizophrenia patients had lower FA (P = 10^-11 ) and faster age-related decline in FA (P = 0.02) compared with controls. Tract-specific heterochronicity measures, that is, abnormal rates of adolescent maturation and aging explained approximately 50% of the regional variance effects of diagnosis and age-by-diagnosis interaction in patients. Interactive, three-dimensional visualization of the results is available at www.enigma-viewer.org.

CONCLUSION

WM tracts that mature later in life appeared more sensitive to the pathophysiology of schizophrenia and were more susceptible to faster age-related decline in FA values. Hum Brain Mapp 37:4673-4688, 2016. © 2016 Wiley Periodicals, Inc.

Genome research in pre-dementia stages of Alzheimer's disease

Genetic characterization of individuals at risk of Alzheimer's disease (AD), i.e. people having amyloid deposits in the brain without symptoms, people suffering from subjective cognitive decline (SCD) or mild cognitive impairment (MCI), has spurred the interests of researchers. However, their pre-dementia genetic profile remains mostly unexplored. In this study, we reviewed the loci related to phenotypes of AD, MCI and SCD from literature and performed the first meta-analyses evaluating the role of apolipoprotein E (APOE) in the risk of conversion from a healthy status to MCI and SCD. For AD dementia risk, an increased number of loci have been identified; to date, 28 genes have been associated with Late Onset AD. In MCI syndrome, APOE is confirmed as a pheno-conversion factor leading from MCI to AD, and clusterin is a promising candidate. Additionally, our meta-analyses revealed APOE as genetic risk factor to convert from a healthy status to MCI [OR = 1.849 (1.587-2.153); P = 2.80  × 10-15] and to a lesser extent from healthy status to SCD [OR = 1.151 (1.015-1.304); P = 0.028]. Thus, we believe that genetic studies in longitudinal SCD and MCI series may provide new therapeutic targets and improve the existing knowledge of AD. This type of studies must be completed on healthy subjects to better understand the natural disease resistance to brain insults and neurodegeneration.

White Matter Microstructural Organization Is Higher with Age in Adult Superior Cerebellar Peduncles

Using diffusion tensor imaging, we conducted an exploratory investigation of the relationship between white matter tract microstructure and age in 200 healthy adult subjects using tract-based spatial statistics (TBSS). Though most tracts showed the slight decline in microstructural organization with age widely noted, in both superior cerebellar peduncles (SCP) it correlated positively with age, a result not previously reported. We confirmed this by using an alternative method, and by repeating our TBSS analysis in an additional sample of 133 healthy adults. In exploring this surprising result we considered the possibility that this might arise from the continual cognitive and motor refinement that is enacted in the cerebellum: we found that tract microstructure in both SCPs was also strongly correlated with IQ, again in contrast with all other tracts, and its relationship with age mediated by IQ, as a training model would predict.

Exome Sequence Data From Multigenerational Families Implicate AMPA Receptor Trafficking in Neurocognitive Impairment and Schizophrenia Risk

Schizophrenia is a mental disorder characterized by impairments in behavior, thought, and neurocognitive performance. We searched for susceptibility loci at a quantitative trait locus (QTL) previously reported for abstraction and mental flexibility (ABF), a cognitive function often compromised in schizophrenia patients and their unaffected relatives. Exome sequences were determined for 134 samples in 8 European American families from the original linkage study, including 25 individuals with schizophrenia or schizoaffective disorder. At chromosome 5q32-35.3, we analyzed 407 protein-altering variants for association with ABF and schizophrenia status. For replication, significant, Bonferroni-corrected findings were tested against cognitive traits in Mexican American families (n = 959), as well as interrogated for schizophrenia risk using GWAS results from the Psychiatric Genomics Consortium (PGC). From the gene SYNPO, rs6579797 (MAF = 0.032) shows significant associations with ABF (P = .015) and schizophrenia (P = .040), as well as jointly (P = .0027). In the Mexican American pedigrees, rs6579797 exhibits significant associations with IQ (P = .011), indicating more global effects on neurocognition. From the PGC results, other SYNPO variants were identified with near significant effects on schizophrenia risk, with a local linkage disequilibrium block displaying signatures of positive selection. A second missense variant within the QTL, rs17551608 (MAF = 0.19) in the gene WWC1, also displays a significant effect on schizophrenia in our exome sequences (P = .038). Remarkably, the protein products of SYNPO and WWC1 are interaction partners involved in AMPA receptor trafficking, a brain process implicated in synaptic plasticity. Our study reveals variants in these genes with significant effects on neurocognition and schizophrenia risk, identifying a potential pathogenic mechanism for schizophrenia spectrum disorders.

Voxel-Based Meta-Analytical Evidence of Structural Disconnectivity in Major Depression and Bipolar Disorder

BACKGROUND

Identification of white matter microstructure differences and similarities between major depression and bipolar disorder is a necessary step to better understand the underlying brain abnormalities in affective disorders and target more effective treatments. However, research has not yet yielded robust conclusions. We report here a meta-analysis of diffusion tensor imaging studies in these conditions.

METHODS

A comprehensive literature search was conducted up to 2014 to identify studies comparing fractional anisotropy (FA) between patients and control subjects. Results were combined to identify white matter abnormalities in major depression (736 patients vs. 668 control subjects) and bipolar disorder (536 patients vs. 489 control subjects). Effect size comparison and conjunction analysis allowed identification of similarities and differences between the disorders.

RESULTS

A significant decrease in FA in the genu of the corpus callosum characterized both conditions. The comparison between unipolar and bipolar disorders revealed a greater decrease in FA in the left posterior cingulum in bipolar disorder. Studies that adopted tract-based spatial statistics methodology showed more pronounced reductions in these regions compared with voxel-based analyses.

CONCLUSIONS

Major depression and bipolar disorder are characterized by abnormalities in white matter tracts of the genu of the corpus callosum that connect the two hemispheres of the prefrontal cortex implicated in mood regulation. Bipolar disorder was associated with reduced white matter integrity in the left posterior cingulum, which may contribute to cognitive impairment described in this condition. Tract-based spatial statistics may be a more sensitive technique to detect white matter abnormalities in these regions compared with voxel-based analyses.

The impact of psychosis on the course of cognition: a prospective, nested case-control study in individuals at clinical high-risk for psychosis

BACKGROUND

Although cognitive deficits in patients with schizophrenia are rooted early in development, the impact of psychosis on the course of cognitive functioning remains unclear. In this study a nested case-control design was used to examine the relationship between emerging psychosis and the course of cognition in individuals ascertained as clinical high-risk (CHR) who developed psychosis during the study (CHR + T).

METHOD

Fifteen CHR + T subjects were administered a neurocognitive battery at baseline and post-psychosis onset (8.04 months, s.d. = 10.26). CHR + T subjects were matched on a case-by-case basis on age, gender, and time to retest with a group of healthy comparison subjects (CNTL, n = 15) and two groups of CHR subjects that did not transition: (1) subjects matched on medication treatment (i.e. antipsychotics and antidepressants) at both baseline and retesting (Meds-matched CHR + NT, n = 15); (2) subjects unmedicated at both assessments (Meds-free CHR + NT, n = 15).

RESULTS

At baseline, CHR + T subjects showed large global neurocognitive and intellectual impairments, along with specific impairments in processing speed, verbal memory, sustained attention, and executive function. These impairments persisted after psychosis onset and did not further deteriorate. In contrast, CHR + NT subjects demonstrated stable mild to no impairments in neurocognitive and intellectual performance, independent of medication treatment.

CONCLUSIONS

Cognition appears to be impaired prior to the emergence of psychotic symptoms, with no further deterioration associated with the onset of psychosis. Cognitive deficits represent trait risk markers, as opposed to state markers of disease status and may therefore serve as possible predictors of schizophrenia prior to the onset of the full illness.

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior.

Perfusion shift from white to gray matter may account for processing speed deficits in schizophrenia

Reduced speed of cerebral information processing is a cognitive deficit associated with schizophrenia. Normal information processing speed (PS) requires intact white matter (WM) physiology to support information transfer. In a cohort of 107 subjects (47/60 patients/controls), we demonstrate that PS deficits in schizophrenia patients are explained by reduced WM integrity, which is measured using diffusion tensor imaging, mediated by the mismatch in WM/gray matter blood perfusion, and measured using arterial spin labeling. Our findings are specific to PS, and testing this hypothesis for patient-control differences in working memory produces no explanation. We demonstrate that PS deficits in schizophrenia can be explained by neurophysiological alterations in cerebral WM. Whether the disproportionately low WM integrity in schizophrenia is due to illness or secondary due to this disorder deserves further examination.

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application.

Genome-wide studies of verbal declarative memory in nondemented older people: the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium

BACKGROUND

Memory performance in older persons can reflect genetic influences on cognitive function and dementing processes. We aimed to identify genetic contributions to verbal declarative memory in a community setting.

METHODS

We conducted genome-wide association studies for paragraph or word list delayed recall in 19 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, comprising 29,076 dementia- and stroke-free individuals of European descent, aged ≥45 years. Replication of suggestive associations (p < 5 × 10(-6)) was sought in 10,617 participants of European descent, 3811 African-Americans, and 1561 young adults.

RESULTS

rs4420638, near APOE, was associated with poorer delayed recall performance in discovery (p = 5.57 × 10(-10)) and replication cohorts (p = 5.65 × 10(-8)). This association was stronger for paragraph than word list delayed recall and in the oldest persons. Two associations with specific tests, in subsets of the total sample, reached genome-wide significance in combined analyses of discovery and replication (rs11074779 [HS3ST4], p = 3.11 × 10(-8), and rs6813517 [SPOCK3], p = 2.58 × 10(-8)) near genes involved in immune response. A genetic score combining 58 independent suggestive memory risk variants was associated with increasing Alzheimer disease pathology in 725 autopsy samples. Association of memory risk loci with gene expression in 138 human hippocampus samples showed cis-associations with WDR48 and CLDN5, both related to ubiquitin metabolism.

CONCLUSIONS

This largest study to date exploring the genetics of memory function in ~40,000 older individuals revealed genome-wide associations and suggested an involvement of immune and ubiquitin pathways.

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees

BACKGROUND

Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees.

METHODS

A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage.

RESULTS

Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia.

CONCLUSIONS

With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.