Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance.

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Clinical correlation but no elevation of striatal dopamine synthesis capacity in two independent cohorts of medication-free individuals with schizophrenia.

Dysregulation of dopamine systems has been considered a foundational driver of pathophysiological processes in schizophrenia, an illness characterized by diverse domains of symptomatology. Prior work observing elevated presynaptic dopamine synthesis capacity in some patient groups has not always identified consistent symptom correlates, and studies of affected individuals in medication-free states have been challenging to obtain. Here we report on two separate cohorts of individuals with schizophrenia spectrum illness who underwent blinded medication withdrawal and medication-free neuroimaging with [18F]-FDOPA PET to assess striatal dopamine synthesis capacity. Consistently in both cohorts, we found no significant differences between patient and matched, healthy comparison groups; however, we did identify and replicate robust inverse relationships between negative symptom severity and tracer-specific uptake widely throughout the striatum: [18F]-FDOPA specific uptake was lower in patients with a greater preponderance of negative symptoms. Complementary voxel-wise and region of interest analyses, both with and without partial volume correction, yielded consistent results. These data suggest that for some individuals, striatal hyperdopaminergia may not be a defining or enduring feature of primary psychotic illness. However, clinical differences across individuals may be significantly linked to variability in striatal dopaminergic tone. These findings call for further experimentation aimed at parsing the heterogeneity of dopaminergic systems function in schizophrenia.

Comparison of Transcranial Sonography and [18 F]-Fluorodopa PET Imaging in GBA1 Mutation Carriers.

BACKGROUND: Mutations in GBA1 are a common genetic risk factor for parkinsonism; however, penetrance is incomplete, and biomarkers of future progression to parkinsonism are needed. Both nigral sonography and striatal [18 F]-FDOPA PET assay dopamine system health, but their utility and coherence in this context are unclear. OBJECTIVE: The aim of this study is to evaluate the utility and coherence of these modalities in GBA1-associated parkinsonism. METHODS: A total of 34 patients with GBA1 mutations (7 with parkinsonism) underwent both transcranial studies for substantia nigra echogenicity and [18 F]-FDOPA PET to determine striatal tracer-specific uptake (Ki ). RESULTS: Larger nigral echogenic areas and reduced striatal Ki were exclusively observed in parkinsonian patients. Sonographic and PET measurements showed strong inverse correlations but only in individuals with clinical parkinsonism. CONCLUSIONS: Close correspondence between nigral echogenicity and striatal presynaptic dopamine synthesis capacity observed only in GBA1 carriers with parkinsonism provides validation that these two modalities may conjointly capture aspects of the biology underlying clinical parkinsonism but raises questions about their utility as predictive tools in at-risk subjects. © 2022 International Parkinson and Movement Disorder Society.

A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space.

We propose a novel optimization framework that integrates imaging and genetics data for simultaneous biomarker identification and disease classification. The generative component of our model uses a dictionary learning framework to project the imaging and genetic data into a shared low dimensional space. We have coupled both the data modalities by tying the linear projection coefficients to the same latent space. The discriminative component of our model uses logistic regression on the projection vectors for disease diagnosis. This prediction task implicitly guides our framework to find interpretable biomarkers that are substantially different between a healthy and disease population. We exploit the interconnectedness of different brain regions by incorporating a graph regularization penalty into the joint objective function. We also use a group sparsity penalty to find a representative set of genetic basis vectors that span a low dimensional space where subjects are easily separable between patients and controls. We have evaluated our model on a population study of schizophrenia that includes two task fMRI paradigms and single nucleotide polymorphism (SNP) data. Using ten-fold cross validation, we compare our generative-discriminative framework with canonical correlation analysis (CCA) of imaging and genetics data, parallel independent component analysis (pICA) of imaging and genetics data, random forest (RF) classification, and a linear support vector machine (SVM). We also quantify the reproducibility of the imaging and genetics biomarkers via subsampling. Our framework achieves higher class prediction accuracy and identifies robust biomarkers. Moreover, the implicated brain regions and genetic variants underlie the well documented deficits in schizophrenia.

Beyond linearity in neuroimaging: Capturing nonlinear relationships with application to longitudinal studies.

The ubiquitous adoption of linearity for quantitative predictors in statistical modeling is likely attributable to its advantages of straightforward interpretation and computational feasibility. The linearity assumption may be a reasonable approximation especially when the variable is confined within a narrow range, but it can be problematic when the variable's effect is non-monotonic or complex. Furthermore, visualization and model assessment of a linear fit are usually omitted because of challenges at the whole brain level in neuroimaging. By adopting a principle of learning from the data in the presence of uncertainty to resolve the problematic aspects of conventional polynomial fitting, we introduce a flexible and adaptive approach of multilevel smoothing splines (MSS) to capture any nonlinearity of a quantitative predictor for population-level neuroimaging data analysis. With no prior knowledge regarding the underlying relationship other than a parsimonious assumption about the extent of smoothness (e.g., no sharp corners), we express the unknown relationship with a sufficient number of smoothing splines and use the data to adaptively determine the specifics of the nonlinearity. In addition to introducing the theoretical framework of MSS as an efficient approach with a counterbalance between flexibility and stability, we strive to (a) lay out the specific schemes for population-level nonlinear analyses that may involve task (e.g., contrasting conditions) and subject-grouping (e.g., patients vs controls) factors; (b) provide modeling accommodations to adaptively reveal, estimate and compare any nonlinear effects of a predictor across the brain, or to more accurately account for the effects (including nonlinear effects) of a quantitative confound; (c) offer the associated program 3dMSS to the neuroimaging community for whole-brain voxel-wise analysis as part of the AFNI suite; and (d) demonstrate the modeling approach and visualization processes with a longitudinal dataset of structural MRI scans.

The NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty: Protocol and rationale for methods and measures.

Delineating the relationship between human neurodevelopment and the maturation of the hypothalamic-pituitary-gonadal (HPG) axis during puberty is critical for investigating the increase in vulnerability to neuropsychiatric disorders that is well documented during this period. Preclinical research demonstrates a clear association between gonadal production of sex steroids and neurodevelopment; however, identifying similar associations in humans has been complicated by confounding variables (such as age) and the coactivation of two additional endocrine systems (the adrenal androgenic system and the somatotropic growth axis) and requires further elucidation. In this paper, we present the design of, and preliminary observations from, the ongoing NIMH Intramural Longitudinal Study of the Endocrine and Neurobiological Events Accompanying Puberty. The aim of this study is to directly examine how the increase in sex steroid hormone production following activation of the HPG-axis (i.e., gonadarche) impacts neurodevelopment, and, additionally, to determine how gonadal development and maturation is associated with longitudinal changes in brain structure and function in boys and girls. To disentangle the effects of sex steroids from those of age and other endocrine events on brain development, our study design includes 1) selection criteria that establish a well-characterized baseline cohort of healthy 8-year-old children prior to the onset of puberty (e.g., prior to puberty-related sex steroid hormone production); 2) temporally dense longitudinal, repeated-measures sampling of typically developing children at 8-10 month intervals over a 10-year period between the ages of eight and 18; 3) contemporaneous collection of endocrine and other measures of gonadal, adrenal, and growth axis function at each timepoint; and 4) collection of multimodal neuroimaging measures at these same timepoints, including brain structure (gray and white matter volume, cortical thickness and area, white matter integrity, myelination) and function (reward processing, emotional processing, inhibition/impulsivity, working memory, resting-state network connectivity, regional cerebral blood flow). This report of our ongoing longitudinal study 1) provides a comprehensive review of the endocrine events of puberty; 2) details our overall study design; 3) presents our selection criteria for study entry (e.g., well-characterized prepubertal baseline) along with the endocrinological considerations and guiding principles that underlie these criteria; 4) describes our longitudinal outcome measures and how they specifically relate to investigating the effects of gonadal development on brain development; and 5) documents patterns of fMRI activation and resting-state networks from an early, representative subsample of our cohort of prepubertal 8-year-old children.

Longitudinal Positron Emission Tomography of Dopamine Synthesis in Subjects with GBA1 Mutations.

Mutations in GBA1, the gene mutated in Gaucher disease, are a common genetic risk factor for Parkinson disease, although the penetrance is low. We performed [18 F]-fluorodopa positron emission tomography studies of 57 homozygous and heterozygous GBA1 mutation carriers (15 with parkinsonism) and 98 controls looking for early indications of dopamine loss using voxelwise analyses to identify group differences in striatal [18 F]-fluorodopa uptake (Ki ). Forty-eight subjects were followed longitudinally. Cross-sectional and longitudinal comparisons of Ki and Ki change found significant effects of Parkinson disease. However, at baseline and over time, striatal [18 F]-fluorodopa uptake in mutation carriers without parkinsonism did not significantly differ from controls. ANN NEUROL 2020;87:652-657.

Epigenetic intersection of BDNF Val66Met genotype with premenstrual dysphoric disorder transcriptome in a cross-species model of estradiol add-back.

Premenstrual dysphoric disorder (PMDD) affects over 5% of women, with symptoms similar to anxiety and major depression, and is associated with differential sensitivity to circulating ovarian hormones. Little is known about the genetic and epigenetic factors that increase the risk to develop PMDD. We report that 17ß-estradiol (E2) affects the behavior and the epigenome in a mouse model carrying a single-nucleotide polymorphism of the brain-derived neurotrophic factor gene (BDNF Val66Met), in a way that recapitulates the hallmarks of PMDD. Ovariectomized mice heterozygous for the BDNF Met allele (Het-Met) and their matched wild-type (WT) mice were administered estradiol or vehicle in drinking water for 6 weeks. Using the open field and the splash test, we show that E2 add-back induces anxiety-like and depression-like behavior in Het-Met mice, but not in WT mice. RNA-seq of the ventral hippocampus (vHpc) highlights that E2-dependent gene expression is markedly different between WT mice and Het-Met mice. Through a comparative whole-genome RNA-seq analysis between mouse vHpc and lymphoblastoid cell line cultures from control women and women with PMDD, we discovered common epigenetic biomarkers that transcend species and cell types. Those genes include epigenetic modifiers of the ESC/E(Z) complex, an effector of response to ovarian steroids. Although the BDNF Met genotype intersects the behavioral and transcriptional traits of women with PMDD, we suggest that these similarities speak to the epigenetic factors by which ovarian steroids produce negative behavioral effects.

KCNH2-3.1 mediates aberrant complement activation and impaired hippocampal-medial prefrontal circuitry associated with working memory deficits.

Increased expression of the 3.1 isoform of the KCNH2 potassium channel has been associated with cognitive dysfunction and with schizophrenia, yet little is known about the underlying pathophysiological mechanisms. Here, by using in vivo wireless local field potential recordings during working memory processing, in vitro brain slice whole-cell patching recordings and in vivo stereotaxic hippocampal injection of AAV-encoded expression, we identified specific and delayed disruption of hippocampal-mPFC synaptic transmission and functional connectivity associated with reductions of SERPING1, CFH, and CD74 in the KCNH2-3.1 overexpression transgenic mice. The differentially expressed genes in mice are enriched in neurons and microglia, and reduced expression of these genes dysregulates the complement cascade, which has been previously linked to synaptic plasticity. We find that knockdown of these genes in primary neuronal-microglial cocultures from KCNH2-3.1 mice impairs synapse formation, and replenishing reduced CFH gene expression rescues KCNH2-3.1-induced impaired synaptogenesis. Translating to humans, we find analogous dysfunctional interactions between hippocampus and prefrontal cortex in coupling of the fMRI blood oxygen level-dependent (BOLD) signal during working memory in healthy subjects carrying alleles associated with increased KCNH2-3.1 expression in brain. Our data uncover a previously unrecognized role of the truncated KCNH2-3.1 potassium channel in mediating complement activation, which may explain its association with altered hippocampal-prefrontal connectivity and synaptic function. These results provide a potential molecular link between increased KCNH2-3.1 expression, synapse alterations, and hippocampal-prefrontal circuit abnormalities implicated in schizophrenia.

Neanderthal-derived genetic variation in living humans relates to schizophrenia diagnosis, to psychotic symptom severity, and to dopamine synthesis.

Schizophrenia has been hypothesized to be a human-specific condition, but experimental approaches to testing this idea have been limited. Because Neanderthals, our closest evolutionary relatives, interbred with modern humans prior to their disappearance from the fossil record, leaving a residual echo that survives in our DNA today, we leveraged new discoveries about ancient hominid DNA to explore this hypothesis in living people in three converging ways. First, in four independent case-control datasets totaling 9,362 individuals, individuals with schizophrenia had less Neanderthal-derived genetic variation than controls (p = .044). Second, in 49 unmedicated inpatients with schizophrenia, having more Neanderthal admixture predicted less severe positive symptoms (p = .046). Finally, using 18 F-fluorodopa PET scanning in 172 healthy individuals, having greater Neanderthal introgression was significantly associated with lower dopamine synthesis capacity in the striatum and pons (p's < 2 × 10-5 ), which is fundamentally important in the pathophysiology and treatment of psychosis. These results may help to elucidate the evolutionary history of a devastating neuropsychiatric disease by supporting the notion of schizophrenia as a human-specific condition. Additionally, the relationship between Neanderthal admixture and dopamine function suggests a potential mechanism whereby Neanderthal admixture may have affected our gene pool to alter schizophrenia risk and/or course.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Williams syndrome hemideletion and LIMK1 variation both affect dorsal stream functional connectivity.

Williams syndrome is a rare genetic disorder caused by hemizygous deletion of ∼1.6 Mb affecting 26 genes on chromosome 7 (7q11.23) and is clinically typified by two cognitive/behavioural hallmarks: marked visuospatial deficits relative to verbal and non-verbal reasoning abilities and hypersocial personality. Clear knowledge of the circumscribed set of genes that are affected in Williams syndrome, along with the well-characterized neurobehavioural phenotype, offers the potential to elucidate neurogenetic principles that may apply in genetically and clinically more complex settings. The intraparietal sulcus, in the dorsal visual processing stream, has been shown to be structurally and functionally altered in Williams syndrome, providing a target for investigating resting-state functional connectivity and effects of specific genes hemideleted in Williams syndrome. Here, we tested for effects of the LIMK1 gene, deleted in Williams syndrome and important for neuronal maturation and migration, on intraparietal sulcus functional connectivity. We first defined a target brain phenotype by comparing intraparietal sulcus resting functional connectivity in individuals with Williams syndrome, in whom LIMK1 is hemideleted, with typically developing children. Then in two separate cohorts from the general population, we asked whether intraparietal sulcus functional connectivity patterns similar to those found in Williams syndrome were associated with sequence variation of the LIMK1 gene. Four independent between-group comparisons of resting-state functional MRI data (total n = 510) were performed: (i) 20 children with Williams syndrome compared to 20 age- and sex-matched typically developing children; (ii) a discovery cohort of 99 healthy adults stratified by LIMK1 haplotype; (iii) a replication cohort of 32 healthy adults also stratified by LIMK1 haplotype; and (iv) 339 healthy adolescent children stratified by LIMK1 haplotype. For between-group analyses, differences in intraparietal sulcus resting-state functional connectivity were calculated comparing children with Williams syndrome to matched typically developing children and comparing LIMK1 haplotype groups in each of the three general population cohorts separately. Consistent with the visuospatial construction impairment and hypersocial personality that typify Williams syndrome, the Williams syndrome cohort exhibited opposite patterns of intraparietal sulcus functional connectivity with visual processing regions and social processing regions: decreased circuit function in the former and increased circuit function in the latter. All three general population groups also showed LIMK1 haplotype-related differences in intraparietal sulcus functional connectivity localized to the fusiform gyrus, a visual processing region also identified in the Williams syndrome-typically developing comparison. These results suggest a neurogenetic mechanism, in part involving LIMK1, that may bias neural circuit function in both the general population and individuals with Williams syndrome.

Sequence Variation Associated with SLC12A5 Gene Expression Is Linked to Brain Structure and Function in Healthy Adults.

A single-nucleotide polymorphism in the promoter region of the Matrix Metalloproteinase-9 (MMP9) gene, rs3918242, has been shown to affect MMP9 expression in macrophages and was associated with schizophrenia by two independent groups. However, rs3918242's effects on MMP9 expression were not replicable in cell lines or brain tissue. Additionally, publically available data indicate that rs3918242 genotype is related not to MMP9 expression, but rather to expression of SLC12A5, a nearby gene coding for a K+/Cl- cotransporter, whose expression has also been related to schizophrenia. Here, we studied brain structure and function in healthy participants stratified by rs3918242 genotype using structural MRI (N = 298), functional MRI during an N-back working memory task (N = 554), and magnetoencephalography (MEG) during the same task (N = 190). We found rs3918242 was associated with gray matter volume (GMV) in the insula and dorsolateral prefrontal cortex bilaterally, closely replicated in discovery and replication samples; and with inferior parietal lobule (IPL) GMV when the samples were meta-analytically combined. Additionally, using both fMRI and MEG, rs3918242 was associated with right IPL working memory-related activation, replicated in two cohorts and across imaging modalities. These convergent results provide further impetus for examinations of the relationship of SLC12A5 with brain structure and function in neuropsychiatric disease.

Schizophrenia polygenic risk score predicts mnemonic hippocampal activity.

The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.

Evaluation of incidental pelvic fluid in relation to physiological changes in healthy pubescent children using pelvic magnetic resonance imaging.

BACKGROUND: Peritoneal free fluid can indicate an underlying disease process; however detection of minimal peritoneal free fluid in healthy children is not uncommon. OBJECTIVE: To assess the significance of incidental peritoneal free fluid within healthy children by MRI and its relation to physiological changes during puberty. MATERIALS AND METHODS: This prospective study was performed on 32 healthy volunteers (20 boys) between the ages of 8 years and 13 years, with consecutive follow-ups every 8-10 months for an average of 3 years. Body mass index (BMI) z-score, pubertal status, C-reactive protein and sex hormone concentrations were assessed prior to MRI studies. We reviewed a total of 120 pelvic MRI studies (61 boys) and measured the quantity of peritoneal free fluid. For statistical analysis we used linear mixed-model accounting for within-patient correlations. RESULTS: The mean ± standard deviation volume of peritoneal free fluid was 4.7±5.7 mL in girls and 1.9±3.1 mL in boys, with a maximum volume of 25 mL and 17 mL, respectively. The prevalence of peritoneal free fluid was significantly higher in girls (91%) compared to boys (67%; P=0.0035). In 15% of the girls and 3% of the boys the fluid was greater than 10 mL. The mean volume of peritoneal free fluid in the fourth stage of puberty was higher and significantly different from the mean volume in the first stage of puberty (P=0.01). CONCLUSION: Among healthy pubescent children, the prevalence of peritoneal free fluid is significantly higher in girls. The volume of peritoneal free fluid can reach volumes greater than 10 mL during normal puberty, especially in the fourth stage, and can be assumed normal in the absence of active disease.

A method for determining haploid and triploid genotypes and their association with vascular phenotypes in Williams syndrome and 7q11.23 duplication syndrome.

BACKGROUND: Williams syndrome ([WS], 7q11.23 hemideletion) and 7q11.23 duplication syndrome (Dup7) show contrasting syndromic symptoms. However, within each group there is considerable interindividual variability in the degree to which these phenotypes are expressed. Though software exists to identify areas of copy number variation (CNV) from commonly-available SNP-chip data, this software does not provide non-diploid genotypes in CNV regions. Here, we describe a method for identifying haploid and triploid genotypes in CNV regions, and then, as a proof-of-concept for applying this information to explain clinical variability, we test for genotype-phenotype associations. METHODS: Blood samples for 25 individuals with WS and 13 individuals with Dup7 were genotyped with Illumina-HumanOmni5M SNP-chips. PennCNV and in-house code were used to make genotype calls for each SNP in the 7q11.23 locus. We tested for association between the presence of aortic arteriopathy and genotypes of the remaining (haploid in WS) or duplicated (triploid in Dup7) alleles. RESULTS: Haploid calls in the 7q11.23 region were made for 99.0% of SNPs in the WS group, and triploid calls for 98.8% of SNPs in those with Dup7. The G allele of SNP rs2528795 in the ELN gene was associated with aortic stenosis in WS participants (p < 0.0049) while the A allele of the same SNP was associated with aortic dilation in Dup7. CONCLUSIONS: Commonly available SNP-chip information can be used to make haploid and triploid calls in individuals with CNVs and then to relate variability in specific genes to variability in syndromic phenotypes, as demonstrated here using aortic arteriopathy. This work sets the stage for similar genotype-phenotype analyses in CNVs where phenotypes may be more complex and/or where there is less information about genetic mechanisms.

Brain-Derived Neurotrophic Factor Val66Met Polymorphism Affects the Relationship Between an Anxiety-Related Personality Trait and Resting Regional Cerebral Blood Flow.

Brain-derived neurotrophic factor (BDNF) is an important modulator of constitutive stress responses mediated by limbic frontotemporal circuits, and its gene contains a functional polymorphism (Val66Met) that may influence trait stress sensitivity. Reports of an association of this polymorphism with anxiety-related personality traits have been controversial and without clear neurophysiological support. We, therefore, determined the relationship between resting regional cerebral blood flow (rCBF) and a well-validated measure of anxiety-related personality, the TPQ Harm Avoidance (HA) scale, as a function of BDNF Val66Met genotype. Sixty-four healthy participants of European ancestry underwent resting H215O positron emission tomography scans. For each genotype group separately, we first determined the relationship between participants' HA scores and their resting rCBF values in each voxel across the entire brain, and then directly compared these HA-rCBF relationships between Val66Met genotype groups. HA-rCBF relationships differed between Val homozygotes and Met carriers in several regions relevant to stress regulation: subgenual cingulate, orbital frontal cortex, and the hippocampal/parahippocampal region. In each of these areas, the relationship was positive in Val homozygotes and negative in Met carriers. These data demonstrate a coupling between trait anxiety and basal resting blood flow in frontolimbic neurocircuitry that may be determined in part by genetically mediated BDNF signaling.

BDNF Val66Met polymorphism tunes frontolimbic circuitry during affective contextual learning.

Adaptive learning impairments are common in cognitive and behavioral disorders, but the neurogenetic mechanisms supporting human affective learning are poorly understood. We designed a higher-order contextual learning task in which healthy participants genotyped for the Val66Met polymorphism of the brain derived neurotropic factor gene (BDNF) were required to choose the member of a picture pair most congruent with the emotion in a previously-viewed facial expression video in order to produce an advantageous monetary outcome. Functional magnetic resonance imaging (fMRI) identified frontolimbic blood oxygenation level dependent (BOLD) reactivity that was associated with BDNF Val66Met genotype during all three phases of the learning task: aversive and reward-predictive learning, contextually-challenging decision-making, and choice-related monetary loss-avoidance and gain outcomes. Relative to Val homozygotes, Met carriers showed attenuated ventromedial prefrontal response to predictive affective cues, dorsolateral prefrontal signaling that depended on decision difficulty, and enhanced ventromedial prefrontal reactivity that was specific to loss-avoidance. These findings indicate that the BDNF Val66Met polymorphism is associated with functional tuning of behaviorally-relevant frontolimbic circuitry, particularly involving the ventromedial prefrontal cortex, during higher-order learning.

Retrospective correction of frequency drift in spectral editing: The GABA editing example.

GABA levels can be measured using proton MRS with a two-step editing sequence. However due to the low concentration of GABA, long acquisition time is usually needed to achieve sufficient SNR to detect small differences in many psychiatric disorders. During this long scan time the frequency offset of the measured voxel can change because of magnetic field drift and patient movement. This drift will change the frequency of the editing pulse relative to that of metabolites, leading to errors in quantification. In this article we describe a retrospective method to correct for frequency drift in spectral editing. A series of reference signals for each metabolite was generated for a range of frequency offsets and then averaged together based on the history of frequency changes over the scan. These customized basis sets were used to fit the in vivo data. Our results demonstrate the effectiveness of the correction method and the remarkable robustness of a GABA editing technique with a top hat editing profile in the presence of frequency drift.

Convergent BOLD and Beta-Band Activity in Superior Temporal Sulcus and Frontolimbic Circuitry Underpins Human Emotion Cognition.

The processing of social information in the human brain is widely distributed neuroanatomically and finely orchestrated over time. However, a detailed account of the spatiotemporal organization of these key neural underpinnings of human social cognition remains to be elucidated. Here, we applied functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same participants to investigate spatial and temporal neural patterns evoked by viewing videos of facial muscle configurations. We show that observing the emergence of expressions elicits sustained blood oxygenation level-dependent responses in the superior temporal sulcus (STS), a region implicated in processing meaningful biological motion. We also found corresponding event-related changes in sustained MEG beta-band (14-30 Hz) oscillatory activity in the STS, consistent with the possible role of beta-band activity in visual perception. Dynamically evolving fearful and happy expressions elicited early (0-400 ms) transient beta-band activity in sensorimotor cortex that persisted beyond 400 ms, at which time it became accompanied by a frontolimbic spread (400-1000 ms). In addition, individual differences in sustained STS beta-band activity correlated with speed of emotion recognition, substantiating the behavioral relevance of these signals. This STS beta-band activity showed valence-specific coupling with the time courses of facial movements as they emerged into full-blown fearful and happy expressions (negative and positive coupling, respectively). These data offer new insights into the perceptual relevance and orchestrated function of the STS and interconnected pathways in social-emotion cognition.