Genetic analysis of cortical thickness and fractional anisotropy of water diffusion in the brain

Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI

Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan, complementing the process of gray matter development and degeneration. Here, we create normative lifespan reference curves for global and regional WM microstructure by harmonizing diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three harmonization methods on regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with known WM maturation peaks. Lifespan FA reference curves were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are publicly available as eHarmonize (https://github.com/ahzhu/eharmonize).

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

RORA rs8042149 polymorphism moderates the association between PTSD symptom severity and transverse temporal gyrus thickness in Han Chinese adults who lost their only child

BACKGROUND

The G allele in retinoid-related orphan receptor alpha (RORA, rs8042149) gene is associated with post-traumatic stress disorder (PTSD) diagnosis and more severe symptoms, reported in the first genome-wide association study of PTSD and subsequent replication studies. Although recent MRI studies identified brain structural deficits in RORA rs8042149 risk G allele carriers, the neural mechanism underlying RORA-related brain structural changes in PTSD remains poorly understood.

METHODS

This study included 227 Han Chinese adults who lost their only child. Cortical thickness and subcortical volume were extracted using FreeSurfer, and PTSD severity was assessed using the Clinician-Administered PTSD Scale. Hierarchical linear regression was used to assess the interaction effect between RORA genotypes (T/T, G/T, and G/G) and PTSD severity on cortical and subcortical structures.

RESULTS

Significant genotype × PTSD symptom severity interaction effects were found for bilateral transverse temporal gyrus thickness. For individuals with the homozygous T/T genotype, current PTSD symptom severity was positively associated with bilateral transverse temporal gyrus thickness. For individuals with heterozygous G/T genotype, current PTSD symptom severity was negatively associated with the left transverse temporal gyrus thickness. No significant main or interaction effects were found in any subcortical regions.

LIMITATION

Cross-sectional design of this study.

CONCLUSION

These findings suggest that the non-risk T/T genotype - but not the risk G allele carriers - has a potentially protective or compensatory role on temporal gyrus thickness in adults who lost their only child. These results highlight the moderation effect of RORA polymorphism on the relationship between PTSD symptom severity and cortical structural changes.

Inter- and intra-individual variation in brain structural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.

Gene co-expression changes underlying the functional connectomic alterations in Alzheimer's disease

BACKGROUND

There is growing evidence indicating that a number of functional connectivity networks are disrupted at each stage of the full clinical Alzheimer's disease spectrum. Such differences are also detectable in cognitive normal (CN) carrying mutations of AD risk genes, suggesting a substantial relationship between genetics and AD-altered functional brain networks. However, direct genetic effect on functional connectivity networks has not been measured.

METHODS

Leveraging existing AD functional connectivity studies collected in NeuroSynth, we performed a meta-analysis to identify two sets of brain regions: ones with altered functional connectivity in resting state network and ones without. Then with the brain-wide gene expression data in the Allen Human Brain Atlas, we applied a new biclustering method to identify a set of genes with differential co-expression patterns between these two set of brain regions.

RESULTS

Differential co-expression analysis using biclustering method led to a subset of 38 genes which showed distinctive co-expression patterns between AD-related and non AD-related brain regions in default mode network. More specifically, we observed 4 sub-clusters with noticeable co-expression difference, where the difference in correlations is above 0.5 on average.

CONCLUSIONS

This work applies a new biclustering method to search for a subset of genes with altered co-expression patterns in AD-related default mode network regions. Compared with traditional differential expression analysis, differential co-expression analysis yielded many more significant hits with extra insights into the wiring mechanism between genes. Particularly, the differential co-expression pattern was observed between two sets of genes, suggesting potential upstream genetic regulators in AD development.

The additive impact of cardio-metabolic disorders and psychiatric illnesses on accelerated brain aging

Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio‐metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning “BrainAge” index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD− (N = 964), SMI−/CMD+ (N = 3,765), SMI−/CMD− (N = 8,083). SMI (F = 40.47, p = 2.06 × 10⁻¹⁰) and CMD (F = 24.69, p = 6.82 × 10⁻⁷) significantly, independently impacted whole‐brain QRI in SMI+. SSD had the largest effect (Cohen’s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI− (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole‐brain QRI was significantly (p < 10⁻¹⁶) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p < 10⁻¹⁶). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio‐metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age‐related cognitive decline.

Sex Chromosome Dosage Effects on White Matter Structure in the Human Brain

Sex chromosome aneuploidies, a group of neurogenetic conditions characterized by aberrant sex chromosome dosage (SCD), are associated with increased risks for psychopathology as well as alterations in gray matter structure. However, we still lack a comprehensive understanding of potential SCD-associated changes in white matter structure, or knowledge of how these changes might relate to known alterations in gray matter anatomy. Thus, here, we use voxel-based morphometry on structural neuroimaging data to provide the first comprehensive maps of regional white matter volume (WMV) changes across individuals with varying SCD (n = 306). We show that mounting X- and Y-chromosome dosage are both associated with widespread WMV decreases, including in cortical, subcortical, and cerebellar tracts, as well as WMV increases in the genu of the corpus callosum and posterior thalamic radiation. We also correlate X- and Y-chromosome-linked WMV changes in certain regions to measures of internalizing and externalizing psychopathology. Finally, we demonstrate that SCD-driven WMV changes show a coordinated coupling with SCD-driven gray matter volume changes. These findings represent the most complete maps of X- and Y-chromosome effects on human white matter to date, and show how such changes connect to psychopathological symptoms and gray matter anatomy.

Multiscale Neuroscience of Psychiatric Disorders

The human brain comprises a multiscale network with multiple levels of organization. Neurons with dendritic and axonal connections form the microscale fabric of brain circuitry, and macroscale brain regions and white matter connections form the infrastructure for system-level brain communication and information integration. In this review, we discuss the emerging trend of multiscale neuroscience, the multidisciplinary field that brings together data from these different levels of nervous system organization to form a better understanding of between-scale relationships of brain structure, function, and behavior in health and disease. We provide a broad overview of this developing field and discuss recent findings of exemplary multiscale neuroscience studies that illustrate the importance of studying cross-scale interactions among the genetic, molecular, cellular, and macroscale levels of brain circuitry and connectivity and behavior. We particularly consider a central, overarching goal of these multiscale neuroscience studies of human brain connectivity: to obtain insight into how disease-related alterations at one level of organization may underlie alterations observed at other scales of brain network organization in mental disorders. We conclude by discussing the current limitations, challenges, and future directions of the field.

Associations and Heritability of Auditory Encoding, Gray Matter, and Attention in Schizophrenia

BACKGROUND

Auditory encoding abnormalities, gray-matter loss, and cognitive deficits are all candidate schizophrenia (SZ) endophenotypes. This study evaluated associations between and heritability of auditory network attributes (function and structure) and attention in healthy controls (HC), SZ patients, and unaffected relatives (UR).

METHODS

Whole-brain maps of M100 auditory activity from magnetoencephalography recordings, cortical thickness (CT), and a measure of attention were obtained from 70 HC, 69 SZ patients, and 35 UR. Heritability estimates (h2r) were obtained for M100, CT at each group-difference region, and the attention measure.

RESULTS

SZ patients had weaker bilateral superior temporal gyrus (STG) M100 responses than HC and a weaker right frontal M100 response than UR. Abnormally large M100 responses in left superior frontal gyrus were observed in UR and SZ patients. SZ patients showed smaller CT in bilateral STG and right frontal regions. Interrelatedness between 3 putative SZ endophenotypes was demonstrated, although in the left STG the M100 and CT function-structure associations observed in HC and UR were absent in SZ patients. Heritability analyses also showed that right frontal M100 and bilateral STG CT measures are significantly heritable.

CONCLUSIONS

Present findings indicated that the 3 SZ endophenotypes examined are not isolated markers of pathology but instead are connected. The pattern of auditory encoding group differences and the pattern of brain function-structure associations differ as a function of brain region, indicating the need for regional specificity when studying these endophenotypes, and with the presence of left STG function-structure associations in HC and UR but not in SZ perhaps reflecting disease-associated damage to gray matter that disrupts function-structure relationships in SZ.

Linking Cortical and Connectional Pathology in Schizophrenia

Schizophrenia is associated with cortical thickness (CT) deficits and breakdown in white matter microstructure. Whether these pathological processes are related remains unclear. We used multimodal neuroimaging to investigate the relationship between regional cortical thinning and breakdown in adjacent infracortical white matter as a function of age and illness duration. Structural magnetic resonance and diffusion images were acquired in 218 schizophrenia patients and 167 age-matched healthy controls to map CT and fractional anisotropy in regionally adjacent infracortical white matter at various cortical depths. We found a robust and reproducible relationship between thickness and anisotropy deficits, which were inversely correlated across cortical regions (r = -.5, P < .0001): the most anisotropic infracortical white matter was found adjacent to regions with extensive cortical thinning. This pattern was evident in early (20 y: r = -.3, P = .005) and middle life (30 y: r = -.4, P = .004, 40 y: r = -.3, P = .04), but not beyond 50 years (P > .05). Frontal pathology contributed most to this pattern, with cortical thinning in patients compared to controls at all ages (P < .05); in contrast to initially elevated frontal white matter anisotropy in patients at 30 years, followed by rapid white matter decline with age (rate of annual decline; patients: 0.0012, controls 0.0006, P < .001). Our findings point to pathological dependencies between gray and white matter in a large sample of schizophrenia patients. We argue that elevated frontal anisotropy reflects regionally-specific, compensatory responses to cortical thinning, which are eventually overwhelmed with increasing illness duration.

Stage-dependent involvement of ADAM10 and its significance in epileptic seizures

The prevalence of epileptic seizures in Alzheimer's disease (AD) has attracted an increasing amount of attention in recent years, and many cohort studies have found several risk factors associated with the genesis of seizures in AD. Among these factors, young age and severe dementia are seemingly contradictory and independent risk factors, indicating that the pathogenesis of epileptic seizures is, to a certain extent, stage‐dependent. A disintegrin and metalloproteinase domain‐containing protein 10 (ADAM10) is a crucial α‐secretase responsible for ectodomain shedding of its substrates; thus, the function of this protein depends on the biological effects of its substrates. Intriguingly, transgenic models have demonstrated ADAM10 to be associated with epilepsy. Based on the biological effects of its substrates, the potential pathogenic roles of ADAM10 in epileptic seizures can be classified into amyloidogenic processes in the ageing stage and cortical dysplasia in the developmental stage. Therefore, ADAM10 is reviewed here as a stage‐dependent modulator in the pathogenesis of epilepsy. Current data regarding ADAM10 in epileptic seizures were collected and reviewed for potential pathogenic roles (ie amyloidogenic processes and cortical dysplasia) and regulatory mechanisms (ie transcriptional and posttranscriptional regulation). These findings are then discussed in terms of the significance of the stage‐dependent functions of ADAM10 in epilepsy. Several potential targets for seizure control, such as candidate transcription factors and microRNAs that regulate ADAM10, as well as potential genetic screening tools for the early recognition of cortical dysplasia, have been suggested but must be studied in more detail.

Radiogenomics for Precision Medicine With a Big Data Analytics Perspective

Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based substratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways toward optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources toward new knowledge discovery that has the potential to advance precision medicine. The latter requires interdisciplinary efforts that will capitalize the information, know-how, and medical data of newly formed groups fusing different backgrounds and expertise. The objective of this paper is to provide insights with respect to the state-of-the-art research in precision medicine. More specifically, our goal is to highlight the fundamental challenges in emerging fields of radiomics and radiogenomics by reviewing the case studies of Cancer and Alzheimer's disease, describe the computational challenges from a big data analytics perspective, and discuss standardization and open data initiatives that will facilitate the adoption of precision medicine methods and practices.

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).

Genetic influences on neonatal cortical thickness and surface area

Genetic and environmental influences on cortical thickness (CT) and surface area (SA) are thought to vary in a complex and dynamic way across the lifespan. It has been established that CT and SA are genetically distinct in older children, adolescents, and adults, and that heritability varies across cortical regions. Very little, however, is known about how genetic and environmental factors influence infant CT and SA. Using structural MRI, we performed the first assessment of genetic and environmental influences on normal variation of SA and CT in 360 twin neonates. We observed strong and significant additive genetic influences on total SA (a²  = 0.78) and small and nonsignificant genetic influences on average CT (a²  = 0.29). Moreover, we found significant genetic overlap (genetic correlation = 0.65) between these global cortical measures. Regionally, there were minimal genetic influences across the cortex for both CT and SA measures and no distinct patterns of genetic regionalization. Overall, outcomes from this study suggest a dynamic relationship between CT and SA during the neonatal period and provide novel insights into how genetic influences shape cortical structure during early development.

Altered white-matter integrity in unaffected siblings of probands with autism spectrum disorders

Despite the evidence of altered white-matter tract property in individuals with autism spectrum disorder (ASD), little is known about their unaffected siblings. This study aimed to investigate white-matter integrity in unaffected siblings of ASD probands. Thirty-nine unaffected siblings (mean age 15.6 ± 6.0 years; 27 males, 69.2%) and 39 typically developing controls (TDC) (14.2 ± 5.6 years; 26 males, 66.7%) were assessed with diffusion spectrum images and neuropsychological tests. Using the tract-based automatic analysis and the threshold-free cluster weighted (TFCW) scores, we searched for the segments among 76 tracts with the largest difference over the entire brain compared to TDC. Tract integrity was quantified by calculating the mean generalized fractional anisotropy (mGFA) values of the segments with the largest difference in TFCW scores. Unaffected siblings showed reduced mGFA in the bilateral frontal aslant tracts, the right superior longitudinal fasciculus 2 (SLF2), the frontostriatal tracts from the right dorsolateral and left ventrolateral prefrontal cortices, the thalamic radiations of the left ventral and the right dorsal thalamus, the callosal fibers of the splenium, and the increased mGFA of the callosal fibers of the precuneus and the left inferior longitudinal fasciculus. Among these, reduced right SLF2 mGFA was associated with social awareness deficits; impaired frontostriatal tract was associated with internalizing problems, while right frontal aslant tract integrity was associated with visual memory deficits. In conclusion, unaffected siblings showed the aberrant integrity of several white-matter tracts, which were correlated with clinical symptoms and neurocognitive dysfunction. The altered tract integrity could be further examined in the probands with ASD. Hum Brain Mapp 38:6053-6067, 2017. © 2017 Wiley Periodicals, Inc.

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 and genetic correlation between the cerebral cortex and associated white matter connections

The aim of this study is to investigate the genetic influence on the cerebral cortex, based on the analyses of heritability and genetic correlation between grey matter (GM) thickness, derived from structural MR images (sMRI), and associated white matter (WM) connections obtained from diffusion MRI (dMRI). We measured on sMRI the cortical thickness (CT) from a large twin imaging cohort using a surface-based approach (N = 308, average age 22.8 ± 2.3 SD). An ACE model was employed to compute the heritability of CT. WM connections were estimated based on probabilistic tractography using fiber orientation distributions (FOD) from dMRI. We then fitted the ACE model to estimate the heritability of CT and FOD peak measures along WM fiber tracts. The WM fiber tracts where genetic influence was detected were mapped onto the cortical surface. Bivariate genetic modeling was performed to estimate the cross-trait genetic correlation between the CT and the FOD-based connectivity of the tracts associated with the cortical regions. We found some cortical regions displaying heritable and genetically correlated GM thickness and WM connectivity, forming networks under stronger genetic influence. Significant heritability and genetic correlations between the CT and WM connectivity were found in regions including the right postcentral gyrus, left posterior cingulate gyrus, right middle temporal gyri, suggesting common genetic factors influencing both GM and WM. Hum Brain Mapp 37:2331-2347, 2016. © 2016 Wiley Periodicals, Inc.

"RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment

Recent advances in quantitative imaging and "omics" technology have generated a wealth of mineable biological "big data". With the push towards a P4 "predictive, preventive, personalized, and participatory" approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose "radiotranscriptomics" as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

Genetic and Environmental Contributions to Functional Connectivity Architecture of the Human Brain

One of the grand challenges faced by neuroscience is to delineate the determinants of interindividual variation in the comprehensive structural and functional connection matrices that comprise the human connectome. At present, this endeavor appears most tractable at the macroanatomic scale, where intrinsic brain activity exhibits robust patterns of synchrony that recapitulate core functional circuits at the individual level. Here, we use a classical twin study design to examine the heritability of intrinsic functional network properties in 101 twin pairs, including network activity (i.e., variance of a network's specific temporal fluctuations) and internetwork coherence (i.e., correlation between networks' specific temporal fluctuations). Five of 7 networks exhibited significantly heritable (23.3–65.2%) network activity, 6 of the 21 internetwork coherences were significantly heritable (25.6–42.0%), and 11 of the 21 internetwork coherences were significantly influenced by common environmental factors (18.0–47.1%). These results suggest that the source of interindividual variation in functional connectome has a modular architecture: individual modules represented by intrinsic connectivity networks are genetic controlled, while environmental factors influence the interplays between the modules. This work further provides network-specific hypotheses for discovery of the specific genetic and environmental factors influencing functional specialization and integration of the human brain.

Heritability of complex white matter diffusion traits assessed in a population isolate

INTRODUCTION

Diffusion weighted imaging (DWI) methods can noninvasively ascertain cerebral microstructure by examining pattern and directions of water diffusion in the brain. We calculated heritability for DWI parameters in cerebral white (WM) and gray matter (GM) to study the genetic contribution to the diffusion signals across tissue boundaries.

METHODS

Using Old Order Amish (OOA) population isolate with large family pedigrees and high environmental homogeneity, we compared the heritability of measures derived from three representative DWI methods targeting the corpus callosum WM and cingulate gyrus GM: diffusion tensor imaging (DTI), the permeability-diffusivity (PD) model, and the neurite orientation dispersion and density imaging (NODDI) model. These successively more complex models represent the diffusion signal modeling using one, two, and three diffusion compartments, respectively.

RESULTS

We replicated the high heritability of the DTI-based fractional anisotropy (h(2)  = 0.67) and radial diffusivity (h(2)  = 0.72) in WM. High heritability in both WM and GM tissues were observed for the permeability-diffusivity index from the PD model (h(2)  = 0.64 and 0.84), and the neurite density from the NODDI model (h(2)  = 0.70 and 0.55). The orientation dispersion index from the NODDI model was only significantly heritable in GM (h(2)  = 0.68).

CONCLUSION

DWI measures from multicompartmental models were significantly heritable in WM and GM. DWI can offer valuable phenotypes for genetic research; and genes thus identified may reveal mechanisms contributing to mental and neurological disorders in which diffusion imaging anomalies are consistently found. Hum Brain Mapp 37:525-535, 2016. © 2015 Wiley Periodicals, Inc.

Heritability of the limbic networks

Individual differences in cognitive ability and social behaviour are influenced by the variability in the structure and function of the limbic system. A strong heritability of the limbic cortex has been previously reported, but little is known about how genetic factors influence specific limbic networks. We used diffusion tensor imaging tractography to investigate heritability of different limbic tracts in 52 monozygotic and 34 dizygotic healthy adult twins. We explored the connections that contribute to the activity of three distinct functional limbic networks, namely the dorsal cingulum (‘medial default-mode network’), the ventral cingulum and the fornix (‘hippocampal-diencephalic-retrosplenial network’) and the uncinate fasciculus (‘temporo-amygdala-orbitofrontal network’). Genetic and environmental variances were mapped for multiple tract-specific measures that reflect different aspects of the underlying anatomy. We report the highest heritability for the uncinate fasciculus, a tract that underpins emotion processing, semantic cognition, and social behaviour. High to moderate genetic and shared environmental effects were found for pathways important for social behaviour and memory, for example, fornix, dorsal and ventral cingulum. These findings indicate that within the limbic system inheritance of specific traits may rely on the anatomy of distinct networks and is higher for fronto-temporal pathways dedicated to complex social behaviour and emotional processing.

Fast and powerful heritability inference for family-based neuroimaging studies

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software cannot estimate heritability, and yet standard quantitative genetics tools cannot provide essential neuroimaging inferences, like family-wise error corrected voxel-wise or cluster-wise P-values. Moreover, available heritability tools rely on P-values that can be inaccurate with usual parametric inference methods. In this work we develop fast estimation and inference procedures for voxel-wise heritability, drawing on recent methodological results that simplify heritability likelihood computations (Blangero et al., 2013). We review the family of score and Wald tests and propose novel inference methods based on explained sum of squares of an auxiliary linear model. To address problems with inaccuracies with the standard results used to find P-values, we propose four different permutation schemes to allow semi-parametric inference (parametric likelihood-based estimation, non-parametric sampling distribution). In total, we evaluate 5 different significance tests for heritability, with either asymptotic parametric or permutation-based P-value computations. We identify a number of tests that are both computationally efficient and powerful, making them ideal candidates for heritability studies in the massive data setting. We illustrate our method on fractional anisotropy measures in 859 subjects from the Genetics of Brain Structure study.

Shared genetic variance between obesity and white matter integrity in Mexican Americans

Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m²) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h² = 0.58), WC (h² = 0.57), and FA (h² = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors.

Assessment of whole brain white matter integrity in youths and young adults with a family history of substance-use disorders

Individuals with a family history of substance use disorders (FH+) are at a greater risk of developing substance use disorders than their peers with no such family histories (FH-) and this vulnerability is proportional to the number of affected relatives (FH density). The risk for developing substance use disorders peaks during adolescence to early adulthood in the general population, and that is thought to be related to delayed maturation of frontocortical and frontostriatal functional circuits. We hypothesized that FH+ youth and young adults have impaired myelination of frontocortical and frontostriatal white matter tracts. We examined fractional anisotropy (FA) data in 80 FH+ and 34 FH- youths (12.9 ± 1.0 years) and in 25 FH+ and 30 FH- young adults (24.3 ± 3.4 years). FH+ youths had lower FA values in both frontocortical and frontostriatal tracts as well as parietocortical tracts including the anterior, superior and posterior corona radiata and the superior frontal-occipital fasciculus. Moreover, FA values in these tracts were negatively correlated with FH density. FH+ adults had lower FA values in two frontocortical tracts: the genu of the corpus callosum and anterior corona radiata and also significant negative correlations between FA and FH density in these same tracts. In both groups, lower FA values corresponded to higher radial diffusivity suggesting reduced axonal myelination. We interpreted our findings as evidence for impaired myelination of frontal white matter that was proportional to FH density. Our data suggest that deficits may partially resolve with age, paralleling an age-related decline in risk for developing substance use disorders.

Traumatic stress, oxidative stress and post-traumatic stress disorder: neurodegeneration and the accelerated-aging hypothesis

Post-traumatic stress disorder (PTSD) is associated with elevated risk for a variety of age-related diseases and neurodegeneration. In this paper, we review evidence relevant to the hypothesis that chronic PTSD constitutes a form of persistent life stress that potentiates oxidative stress (OXS) and accelerates cellular aging. We provide an overview of empirical studies that have examined the effects of psychological stress on OXS, discuss the stress-perpetuating characteristics of PTSD, and then identify mechanisms by which PTSD might promote OXS and accelerated aging. We review studies on OXS-related genes and the role that they may have in moderating the effects of PTSD on neural integrity and conclude with a discussion of directions for future research on antioxidant treatments and biomarkers of accelerated aging in PTSD.

Assessment of whole brain white matter integrity in youths and young adults with a family history of substance-use disorders

Individuals with a family history of substance use disorders (FH+) are at a greater risk of developing substance use disorders than their peers with no such family histories (FH-) and this vulnerability is proportional to the number of affected relatives (FH density). The risk for developing substance use disorders peaks during adolescence to early adulthood in the general population, and that is thought to be related to delayed maturation of frontocortical and frontostriatal functional circuits. We hypothesized that FH+ youth and young adults have impaired myelination of frontocortical and frontostriatal white matter tracts. We examined fractional anisotropy (FA) data in 80 FH+ and 34 FH- youths (12.9 ± 1.0 years) and in 25 FH+ and 30 FH- young adults (24.3 ± 3.4 years). FH+ youths had lower FA values in both frontocortical and frontostriatal tracts as well as parietocortical tracts including the anterior, superior and posterior corona radiata and the superior frontal-occipital fasciculus. Moreover, FA values in these tracts were negatively correlated with FH density. FH+ adults had lower FA values in two frontocortical tracts: the genu of the corpus callosum and anterior corona radiata and also significant negative correlations between FA and FH density in these same tracts. In both groups, lower FA values corresponded to higher radial diffusivity suggesting reduced axonal myelination. We interpreted our findings as evidence for impaired myelination of frontal white matter that was proportional to FH density. Our data suggest that deficits may partially resolve with age, paralleling an age-related decline in risk for developing substance use disorders.

Multimodal white matter imaging to investigate reduced fractional anisotropy and its age-related decline in schizophrenia

We hypothesized that reduced fractional anisotropy (FA) of water diffusion and its elevated aging-related decline in schizophrenia patients may be caused by elevated hyperintensive white matter (HWM) lesions, by reduced permeability-diffusivity index (PDI), or both. We tested this hypothesis in 40/30 control/patient participants. FA values for the corpus callosum were calculated from high angular resolution diffusion tensor imaging (DTI). Whole-brain volume of HWM lesions was quantified by 3D-T2w-fluid-attenuated inversion recovery (FLAIR) imaging. PDI for corpus callosum was ascertained using multi b-value diffusion imaging (15 b-shells with 30 directions per shell). Patients had significantly lower corpus callosum FA values, and there was a significant age-by-diagnosis interaction. Patients also had significantly reduced PDI but no difference in HWM volume. PDI and HWM volume were significant predictors of FA and captured the diagnosis-related variance. Separately, PDI robustly explained FA variance in schizophrenia patients, but not in controls. Conversely, HWM volume made equally significant contributions to variability in FA in both groups. The diagnosis-by-age effect of FA was explained by a PDI-by-diagnosis interaction. Post hoc testing showed a similar trend for PDI of gray mater. Our study demonstrated that reduced FA and its accelerated decline with age in schizophrenia were explained by pathophysiology indexed by PDI, rather than HWM volume.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

White matter microstructural abnormalities in families multiply affected with bipolar I disorder: a diffusion tensor tractography study

BACKGROUND

White matter (WM) abnormalities are proposed as potential endophenotypic markers of bipolar disorder (BD). In a diffusion tensor imaging (DTI) voxel-based analysis (VBA) study of families multiply affected with BD, we previously reported that widespread abnormalities of fractional anisotropy (FA) are associated with both BD and genetic liability for illness. In the present study, we further investigated the endophenotypic potential of WM abnormalities by applying DTI tractography to specifically investigate tracts implicated in the pathophysiology of BD.

METHOD

Diffusion magnetic resonance imaging (MRI) data were acquired from 19 patients with BD type I from multiply affected families, 21 of their unaffected first-degree relatives and 18 healthy volunteers. DTI tractography was used to identify the cingulum, uncinate fasciculus (UF), arcuate portion of the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), corpus callosum, and the anterior limb of the internal capsule (ALIC). Regression analyses were conducted to investigate the effect of participant group and genetic liability on FA and radial diffusivity (RD) in each tract.

RESULTS

We detected a significant effect of group on both FA and RD in the cingulum, SLF, callosal splenium and ILF driven by reduced FA and increased RD in patients compared to controls and relatives. Increasing genetic liability was associated with decreased FA and increased RD in the UF, and decreased FA in the SLF, among patients.

CONCLUSIONS

WM microstructural abnormalities in limbic, temporal and callosal pathways represent microstructural abnormalities associated with BD whereas alterations in the SLF and UF may represent potential markers of endophenotypic risk.

Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion--a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

The retinoid-related orphan receptor alpha (RORA) gene and fear-related psychopathology

BACKGROUND

This study followed on findings from a recent genome-wide association study of PTSD that implicated the retinoid-related orphan receptor alpha (RORA) gene (Logue et al., 2012) by examining its relationship to broader array of disorders.

METHODS

Using data from the same cohort (N=540), we analyzed patterns of association between 606 single nucleotide polymorphisms (SNPs) spanning the RORA gene and comorbidity factors termed fear, distress (i.e., internalizing factors) and externalizing.

RESULTS

Results showed that rs17303244 was associated with the fear component of internalizing (i.e., defined by symptoms of panic, agoraphobia, specific phobia, and obsessive-compulsive disorder) at a level of significance that withstood correction for gene-wide multiple testing.

LIMITATIONS

The primary limitations were the modest size of the cohort and the absence of a replication sample.

CONCLUSIONS

Results add to a growing literature implicating the RORA gene in a wide range of neuropsychiatric disorders and offer new insight into possible molecular mechanisms of the effects of traumatic stress on the brain and the role of genetic factors in those processes.

Genetics of the connectome

Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.

Acute nicotine administration effects on fractional anisotropy of cerebral white matter and associated attention performance

Introduction: Nicotinic acetylcholine receptors are present in the cerebral white matter (WM). We hypothesized that WM response to nicotine can be detected by diffusion tensor imaging (DTI); and that such responses may be associated with nicotine-led cognitive enhancement in sustained attention.

Methods: A randomized, nicotine-placebo patch, crossover, double-blind clinical trial in two non-overlapping cohorts of smokers was used to test the hypothesis. The discovery cohort consisted of 39 subjects (N = 20/19 controls/schizophrenic patients, age = 36.8 ± 10.1 years) and the replication cohorts consisted of 38 healthy smokers (31.7 ± 10.5 years). WM integrity was measured by fractional anisotropy (FA) values for the whole brain and nine preselected WM tracts using tract-based-spatial-statistics.

Results: Nicotine significantly enhanced FA values for the genu of corpus callosum compared with placebo (ΔFA_genu) (p = 0.01) in smokers with low recent smoking exposure as measured by low average cotinine level. This finding was replicated in the second cohort (p = 0.02). ΔFA_genu values explained 22% of variance in performance of a sustained attention task during the nicotine session (p = 0.006). However, this effect was limited to schizophrenia patients (r = 0.62 and 0.09; p = 0.003 and 0.7 for patients and controls, respectively).

Conclusion: Acute pharmacological influence of nicotine patch on WM integrity appeared present, but was dependent on nicotine intake from recent smoking. Change in the WM integrity in the genu of corpus callosum was associated with a significant proportion of variability of nicotine-led changes in sustained attention/working memory of the smokers. Further studies will be necessary to understand biophysical underpinning of the nicotine-related changes in FA.

A genome-wide association study of post-traumatic stress disorder identifies the retinoid-related orphan receptor alpha (RORA) gene as a significant risk locus

We describe the results of the first genome-wide association study (GWAS) of post-traumatic stress disorder (PTSD) performed using trauma-exposed white non-Hispanic participants from a cohort of veterans and their intimate partners (295 cases and 196 controls). Several single-nucleotide polymorphisms (SNPs) yielded evidence of association. One SNP (rs8042149), located in the retinoid-related orphan receptor alpha gene (RORA), reached genome-wide significance. Nominally significant associations were observed for other RORA SNPs in two African-American replication samples-one from the veteran cohort (43 cases and 41 controls) and another independent cohort (100 cases and 421 controls). However, only the associated SNP from the veteran African-American replication sample survived gene-level multiple-testing correction. RORA has been implicated in prior GWAS studies of psychiatric disorders and is known to have an important role in neuroprotection and other behaviorally relevant processes. This study represents an important step toward identifying the genetic underpinnings of PTSD.

Permeability-diffusivity modeling vs. fractional anisotropy on white matter integrity assessment and application in schizophrenia

INTRODUCTION

Diffusion tensor imaging (DTI) assumes a single pool of anisotropically diffusing water to calculate fractional anisotropy (FA) and is commonly used to ascertain white matter (WM) deficits in schizophrenia. At higher b-values, diffusion-signal decay becomes bi-exponential, suggesting the presence of two, unrestricted and restricted, water pools. Theoretical work suggests that semi-permeable cellular membrane rather than the presence of two physical compartments is the cause. The permeability-diffusivity (PD) parameters measured from bi-exponential modeling may offer advantages, over traditional DTI-FA, in identifying WM deficits in schizophrenia.

METHODS

Imaging was performed in N = 26/26 patients/controls (age = 20-61 years, average age = 40.5 ± 12.6). Imaging consisted of fifteen b-shells: b = 250-3800 s/mm(2) with 30 directions/shell, covering seven slices of mid-sagittal corpus callosum (CC) at 1.7 × 1.7 × 4.6 mm. 64-direction DTI was also collected. Permeability-diffusivity-index (PDI), the ratio of restricted to unrestricted apparent diffusion coefficients, and the fraction of unrestricted compartment (Mu) were calculated for CC and cingulate gray matter (GM). FA values for CC were calculated using tract-based-spatial-statistics.

RESULTS

Patients had significantly reduced PDI in CC (p ≅ 10(- 4)) and cingulate GM (p = 0.002), while differences in CC FA were modest (p ≅ .03). There was no group-related difference in Mu. Additional theoretical-modeling analysis suggested that reduced PDI in patients may be caused by reduced cross-membrane water molecule exchanges.

CONCLUSION

PDI measurements for cerebral WM and GM yielded more robust patient-control differences than DTI-FA. Theoretical work offers an explanation that patient-control PDI differences should implicate abnormal active membrane permeability. This would implicate abnormal activities in ion-channels that use water as substrate for ion exchange, in cerebral tissues of schizophrenia patients.

Topographic hub maps of the human structural neocortical network

Hubs within the neocortical structural network determined by graph theoretical analysis play a crucial role in brain function. We mapped neocortical hubs topographically, using a sample population of 63 young adults. Subjects were imaged with high resolution structural and diffusion weighted magnetic resonance imaging techniques. Multiple network configurations were then constructed per subject, using random parcellations to define the nodes and using fibre tractography to determine the connectivity between the nodes. The networks were analysed with graph theoretical measures. Our results give reference maps of hub distribution measured with betweenness centrality and node degree. The loci of the hubs correspond with key areas from known overlapping cognitive networks. Several hubs were asymmetrically organized across hemispheres. Furthermore, females have hubs with higher betweenness centrality and males have hubs with higher node degree. Female networks have higher small-world indices.

Relation between variants in the neurotrophin receptor gene, NTRK3, and white matter integrity in healthy young adults

The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults is related to common variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain. To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6 ± 2.2 years; range: 20-29 years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity. FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.

Transcriptomics of cortical gray matter thickness decline during normal aging

INTRODUCTION

We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging.

METHODS

Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability.

RESULTS

Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT.

CONCLUSION

Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

Updating the mild encephalitis hypothesis of schizophrenia

Schizophrenia seems to be a heterogeneous disorder. Emerging evidence indicates that low level neuroinflammation (LLNI) may not occur infrequently. Many infectious agents with low overall pathogenicity are risk factors for psychoses including schizophrenia and for autoimmune disorders. According to the mild encephalitis (ME) hypothesis, LLNI represents the core pathogenetic mechanism in a schizophrenia subgroup that has syndromal overlap with other psychiatric disorders. ME may be triggered by infections, autoimmunity, toxicity, or trauma. A 'late hit' and gene-environment interaction are required to explain major findings about schizophrenia, and both aspects would be consistent with the ME hypothesis. Schizophrenia risk genes stay rather constant within populations despite a resulting low number of progeny; this may result from advantages associated with risk genes, e.g., an improved immune response, which may act protectively within changing environments, although they are associated with the disadvantage of increased susceptibility to psychotic disorders. Specific schizophrenic symptoms may arise with instances of LLNI when certain brain functional systems are involved, in addition to being shaped by pre-existing liability factors. Prodrome phase and the transition to a diseased status may be related to LLNI processes emerging and varying over time. The variability in the course of schizophrenia resembles the varying courses of autoimmune disorders, which result from three required factors: genes, the environment, and the immune system. Preliminary criteria for subgrouping neurodevelopmental, genetic, ME, and other types of schizophrenias are provided. A rare example of ME schizophrenia may be observed in Borna disease virus infection. Neurodevelopmental schizophrenia due to early infections has been estimated by others to explain approximately 30% of cases, but the underlying pathomechanisms of transition to disease remain in question. LLNI (e.g. from reactivation related to persistent infection) may be involved and other pathomechanisms including dysfunction of the blood-brain barrier or the blood-CSF barrier, CNS-endogenous immunity and the volume transmission mode balancing wiring transmission (the latter represented mainly by synaptic transmission, which is often described as being disturbed in schizophrenia). Volume transmission is linked to CSF signaling; and together could represent a common pathogenetic link for the distributed brain dysfunction, dysconnectivity, and brain structural abnormalities observed in schizophrenia. In addition, CSF signaling may extend into peripheral tissues via the CSF outflow pathway along brain nerves and peripheral nerves, and it may explain the peripheral topology of neuronal dysfunctions found, like in olfactory dysfunction, dysautonomia, and even in peripheral tissues, i.e., the muscle lesions that were found in 50% of cases. Modulating factors in schizophrenia, such as stress, hormones, and diet, are also modulating factors in the immune response. Considering recent investigations of CSF, the ME schizophrenia subgroup may constitute approximately 40% of cases.

The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging

Although aging is associated with changes in brain structure and cognition it remains unclear which specific structural changes mediate individual cognitive changes. Several studies have reported that white matter (WM) integrity, as assessed by diffusion tensor imaging (DTI), mediates, in part, age-related differences in processing speed (PS). There is less evidence for WM integrity mediating age-related differences in higher order abilities (e.g., memory and executive functions). In 165 typically aging adults (age range 54-89) we show that WM integrity in select cerebral regions is associated with higher cognitive abilities and accounts variance not accounted for by PS or age. Specifically, voxel-wise analyses using tract-based spatial statistics (TBSS) revealed that WM integrity was associated with reasoning, cognitive flexibility and PS, but not memory or word fluency, after accounting for age and gender. While cerebral fractional anisotropy (FA) was only associated with PS; mean (MD), axial (AD) and radial (RD) diffusivity were associated with reasoning and flexibility. Reasoning was selectively associated with left prefrontal AD, while cognitive flexibility was associated with MD, AD and RD throughout the cerebrum. Average WM metrics within select WM regions of interest accounted for 18% and 29% of the variance in reasoning and flexibility, respectively, similar to the amount of variance accounted for by age. WM metrics mediated ~50% of the age-related variance in reasoning and flexibility and different proportions, 11% for reasoning and 44% for flexibility, of the variance accounted for by PS. In sum, (i) WM integrity is significantly, but variably, related to specific higher cognitive abilities and can account for a similar proportion of variance as age, and (ii) while FA is selectively associated with PS; while MD, AD and RD are associated with reasoning, flexibility and PS. This illustrates both the anatomical and cognitive selectivity of structure-cognition relationships in the aging brain.

Testing the hypothesis of accelerated cerebral white matter aging in schizophrenia and major depression

BACKGROUND

Elevated rate of aging-related biological and functional decline, termed "accelerated aging," is reported in patients with schizophrenia (SCZ) and major depressive disorder (MDD). We used diffusion tensor imaging derived fractional anisotropy (FA) as a biomarker of aging-related decline in white matter (WM) integrity to test the hypotheses of accelerated aging in SCZ and MDD.

METHODS

The SCZ cohort comprised 58 SCZ patients and 60 controls (aged 20-60 years). The MDD cohort comprised 136 MDD patients and 351 controls (aged 20-79 years). The main outcome measures were the diagnosis-by-age interaction on whole-brain-averaged WM FA values and FA values from 12 major WM tracts.

RESULTS

Diagnosis-by-age interaction for the whole-brain average FA was significant for the SCZ (p = .04) but not the MDD (p = .80) cohort. Diagnosis-by-age interaction was nominally significant (p<.05) for five WM tracts for SCZ and for none of the tracts in the MDD cohort. Tract-specific heterochronicity of the onset of age-related decline in SCZ demonstrated strong negative correlations with the age-of-peak myelination and the rates of age-related decline obtained from normative sample (r =-.61 and-.80, p<.05, respectively). No such trends existed for MDD cohort.

CONCLUSIONS

Cerebral WM showed accelerated aging in SCZ but not in MDD, suggesting some difference in the pathophysiology underlying their WM aging changes. Tract-specific heterochronicity of WM development modulated presentation of accelerated aging in SCZ: WM tracts that matured later in life appeared more sensitive to the pathophysiology of SCZ and demonstrated more susceptibility to disorder-related accelerated decline in FA values with age. This trend was not observed in MDD cohort.

Characterization of Mexican Americans with mild cognitive impairment and Alzheimer's disease

The purpose of the study was to provide characterization of Mexican Americans who meet criteria for Alzheimer's disease (AD) and mild cognitive impairment (MCI). For the study, 1,069 participants ages 40 and above who self-identified as either non-Hispanic white (n = 633) or Mexican American (n = 436) were recruited using a community-based participatory research approach. Global cognition was assessed via the Mini-Mental State Examination (MMSE), dementia severity by the Clinical Dementia Rating Scale, and depression via the Geriatric Depression Scale 30-item version. Age, gender, education, ApoE ε4 allele frequency, and diabetic diagnoses were also analyzed. The findings showed that Mexican Americans (normal controls, MCI, and AD) were younger, less highly educated, performed more poorly on the MMSE, endorsed more symptoms of depression, were more likely to be diagnosed with diabetes, and possessed the ApoE ε4 allele less frequently. Age was the only significant risk factor for cognitive dysfunction (AD/MCI) among Mexican Americans (OR = 1.06, 95% CI = 1.03-1.09). Age (B = 0.07, std = 0.02, p < 0.001) and ApoE ε4 presence (B = 0.9, std = 0.4, p = 0.02) were significantly related to increased disease severity. Given the rapidly growing and aging Mexican American population, there is a substantial need for research into cognitive aging, MCI, and AD among this ethnic group. The current findings hold important implications for both clinic and research settings and point to additional research needs.

Genetics of ageing-related changes in brain white matter integrity - a review

White matter (WM) plays a vital role in the efficient transfer of information between grey matter regions. Modern imaging techniques such as diffusion tensor imaging (DTI) have enabled the examination of WM microstructural changes across the lifespan, but there is limited knowledge about the role genetics plays in the pattern and aetiology of age-related WM microstructural changes. Family and twin studies suggest that the heritability of WM integrity measures changes over the lifespan, with the common DTI measure, fractional anisotropy (FA), showing moderate to high heritability in adults. However, few heritability studies have been undertaken in older adults. Linkage studies in middle-aged adults suggest that specific regions on chromosomes 3 and 15 may harbour genetic variants for WM integrity. A number of studies have investigated candidate genes, with the APOE ɛ4 polymorphism being the most frequently studied. Although these candidate gene studies suggest associations of particular genes with WM integrity measures in some specific brain regions, the findings remain inconsistent due to differences in their methodologies, samples and the outcome measures used. The APOE ɛ4 allele has been associated with decreased WM integrity (FA) in the cingulum, corpus callosum and parahippocampal gyrus. Only one genome-wide association study of global WM integrity measures in older adults has been published, and reported suggestive single nucleotide polymorphisms await replication. Overall, genetic age-related WM integrity studies are lacking and a concerted effort to examine the genetic determinants of age-related decline in WM integrity is clearly needed to improve our understanding of the ageing brain.

A systematic analysis of genomic changes in Tg2576 mice

Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by intelligence decline, behavioral disorders and cognitive disability. The purpose of this study was to investigate gene expression in AD, based on published microarray data on Tg2576 mice. Hierarchical Cluster Analysis and Gene Ontology were employed to group genes together on the basis of their product characteristics and annotation data. Genes with prominent alterations were clustered into apoptosis and axon guidance pathways. Based on our findings and those of previous studies, we propose that the mitochondria-mediated apoptotic pathway plays a crucial role in the neuronal loss and synaptic dysfunction associated with AD. Furthermore, based on the findings of Positional Gene Enrichment analysis and Gene Set Enrichment analysis, we propose that the regulation of transcription of AD genes may be an important pathogenic factor in this neurodegenerative disease. Our results highlight the importance of genes that could subsequently be examined for their potential as prognostic markers for AD.