Childhood urbanicity is associated with emotional episodic memory-related striatal function and common variation in NTRK2.

BACKGROUND: Childhoods in urban or rural environments may differentially affect the risk of neuropsychiatric disorders, possibly through memory processing and neural response to emotional stimuli. Genetic factors may not only influence individuals' choices of residence but also modulate how the living environment affects responses to episodic memory. METHODS: We investigated the effects of childhood urbanicity on episodic memory in 410 adults (discovery sample) and 72 adults (replication sample) with comparable socioeconomic statuses in Beijing, China, distinguishing between those with rural backgrounds (resided in rural areas before age 12 and relocated to urban areas at or after age 12) and urban backgrounds (resided in cities before age 12). We examined the effect of childhood urbanicity on brain function across encoding and retrieval sessions using an fMRI episodic memory paradigm involving the processing of neutral or aversive pictures. Moreover, genetic association analyses were conducted to understand the potential genetic underpinnings that might contribute to memory processing and neural mechanisms influenced by early-life urban or rural environments. RESULTS: Episodic memory retrieval accuracy for more difficult neutral stimuli was similar between those with urban and rural childhoods, whereas aversive stimuli elicited higher retrieval accuracy in the urban group (P = 0.023). For aversive stimuli, subjects with urban childhood had relatively decreased engagement of the striatum at encoding and decreased engagement of the hippocampus at retrieval. This more efficient striatal encoding of aversive stimuli in those with urban childhoods was associated with common variation in neurotrophic tyrosine kinase receptor type 2 (NTRK2) (right striatum: P = 1.58×10-6). These findings were confirmed in the replication sample. CONCLUSIONS: We suggest that this differential striatal processing of aversive stimuli observed in individuals with urban or rural childhoods may represent mechanisms by which childhood urbanicity may affect brain circuits, heightening behavioral responses to negative stressors associated with urban environments. NTRK2-associated neural processes in the striatum may play a role in these processes.

Quantitative Brain Amyloid PET.

Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.

Changes in patterns of age-related network connectivity are associated with risk for schizophrenia.

Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in first-degree relatives of SCZ patients mostly including unaffected siblings (SIB) with neurotypical controls (NC) at the same age stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Two of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.05). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlates with genetic risk for SCZ and is detectable with MRI in young participants.

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.

Tolcapone Treatment for Cognitive and Behavioral Symptoms in Behavioral Variant Frontotemporal Dementia: A Placebo-Controlled Crossover Study.

BACKGROUND: There are currently no disease-targeted treatments for cognitive or behavioral symptoms in patients with behavioral variant frontotemporal dementia (bvFTD). OBJECTIVE: To determine the effect of tolcapone, a specific inhibitor of Catechol-O-Methyltransferase (COMT), in patients with bvFTD. METHODS: In this randomized, double-blind, placebo-controlled, cross-over study at two study sites, we examined the effect of tolcapone on 28 adult outpatients with bvFTD. The primary outcome was reaction time on the N-back cognitive test. As an imaging outcome, we examined differences in the resting blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal intensity between subjects on placebo versus tolcapone performing the N-back test. Secondary outcomes included measures of cognitive performance and behavioral disturbance using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Neuropsychiatric Inventory-Questionnaire (NPI-Q), and Clinical Global Impressions scale (CGI). RESULTS: Tolcapone was well tolerated and no patients dropped out. The most frequent treatment-related adverse event during tolcapone treatment was elevated liver enzymes (21%). There were no significant differences between tolcapone treatment and placebo in the primary or imaging outcomes. However, there were significant differences between RBANS total scores (p < 0.01), NPI-Q total scores (p = 0.04), and CGI total scores (p = 0.035) between treatment conditions which were driven by differences between baseline and tolcapone conditions. Further, there was a trend toward significance between tolcapone and placebo on the CGI (p = 0.078). CONCLUSIONS: Further study of COMT inhibition and related approaches with longer duration of treatment and larger sample sizes in frontotemporal lobar degeneration-spectrum disorders may be warranted.

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.

Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer's disease.

Late-onset Alzheimer's disease (AD) is a complex age-related neurodegenerative disorder that likely involves epigenetic factors. To better understand the epigenetic state associated with AD, we surveyed 420,852 DNA methylation (DNAm) sites from neurotypical controls (N = 49) and late-onset AD patients (N = 24) across four brain regions (hippocampus, entorhinal cortex, dorsolateral prefrontal cortex and cerebellum). We identified 858 sites with robust differential methylation collectively annotated to 772 possible genes (FDR < 5%, within 10 kb). These sites were overrepresented in AD genetic risk loci (p = 0.00655) and were enriched for changes during normal aging (p < 2.2 × 10-16), and nearby genes were enriched for processes related to cell-adhesion, immunity, and calcium homeostasis (FDR < 5%). To functionally validate these associations, we generated and analyzed corresponding transcriptome data to prioritize 130 genes within 10 kb of the differentially methylated sites. These 130 genes were differentially expressed between AD cases and controls and their expression was associated with nearby DNAm (p < 0.05). This integrated analysis implicates novel genes in Alzheimer's disease, such as ANKRD30B. These results highlight DNAm differences in Alzheimer's disease that have gene expression correlates, further implicating DNAm as an epigenetic mechanism underlying pathological molecular changes associated with AD. Furthermore, our framework illustrates the value of integrating epigenetic and transcriptomic data for understanding complex disease.

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.

Association of a Schizophrenia-Risk Nonsynonymous Variant With Putamen Volume in Adolescents: A Voxelwise and Genome-Wide Association Study.

Importance: Deviation from normal adolescent brain development precedes manifestations of many major psychiatric symptoms. Such altered developmental trajectories in adolescents may be linked to genetic risk for psychopathology. Objective: To identify genetic variants associated with adolescent brain structure and explore psychopathologic relevance of such associations. Design, Setting, and Participants: Voxelwise genome-wide association study in a cohort of healthy adolescents aged 14 years and validation of the findings using 4 independent samples across the life span with allele-specific expression analysis of top hits. Group comparison of the identified gene-brain association among patients with schizophrenia, unaffected siblings, and healthy control individuals. This was a population-based, multicenter study combined with a clinical sample that included participants from the IMAGEN cohort, Saguenay Youth Study, Three-City Study, and Lieber Institute for Brain Development sample cohorts and UK biobank who were assessed for both brain imaging and genetic sequencing. Clinical samples included patients with schizophrenia and unaffected siblings of patients from the Lieber Institute for Brain Development study. Data were analyzed between October 2015 and April 2018. Main Outcomes and Measures: Gray matter volume was assessed by neuroimaging and genetic variants were genotyped by Illumina BeadChip. Results: The discovery sample included 1721 adolescents (873 girls [50.7%]), with a mean (SD) age of 14.44 (0.41) years. The replication samples consisted of 8690 healthy adults (4497 women [51.8%]) from 4 independent studies across the life span. A nonsynonymous genetic variant (minor T allele of rs13107325 in SLC39A8, a gene implicated in schizophrenia) was associated with greater gray matter volume of the putamen (variance explained of 4.21% in the left hemisphere; 8.66; 95% CI, 6.59-10.81; P = 5.35 × 10-18; and 4.44% in the right hemisphere; t = 8.90; 95% CI, 6.75-11.19; P = 6.80 × 10-19) and also with a lower gene expression of SLC39A8 specifically in the putamen (t127 = -3.87; P = 1.70 × 10-4). The identified association was validated in samples across the life span but was significantly weakened in both patients with schizophrenia (z = -3.05; P = .002; n = 157) and unaffected siblings (z = -2.08; P = .04; n = 149). Conclusions and Relevance: Our results show that a missense mutation in gene SLC39A8 is associated with larger gray matter volume in the putamen and that this association is significantly weakened in schizophrenia. These results may suggest a role for aberrant ion transport in the etiology of psychosis and provide a target for preemptive developmental interventions aimed at restoring the functional effect of this mutation.

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.

Genetic risk mechanisms of posttraumatic stress disorder in the human brain.

Posttraumatic stress disorder (PTSD) follows exposure to a traumatic event in susceptible individuals. Recently, genome-wide association studies have identified a number of genetic sequence variants that are associated with the risk of developing PTSD. To follow up on identifying the molecular mechanisms of these risk variants, we performed genotype to RNA sequencing-derived quantitative expression (whole gene, exon, and exon junction levels) analysis in the dorsolateral prefrontal cortex (DLPFC) of normal postmortem human brains. We further investigated genotype-gene expression associations within the amygdala in a smaller independent RNA sequencing (Genotype-Tissue Expression [GTEx]) dataset. Our DLPFC analyses identified significant expression quantitative trait loci (eQTL) associations for a "candidate" PTSD risk SNP rs363276 and the expression of two genes: SLC18A2 and PDZD8, where the PTSD risk/minor allele T was associated with significantly lower levels of gene expression for both genes, in the DLPFC. These eQTL associations were independently confirmed in the amygdala from the GTEx database. Rs363276 "T" carriers also showed significantly increased activity in the amygdala during an emotional face-matching task in healthy volunteers. Taken together, our preliminary findings in normal human brains represent a tractable approach to identify mechanisms by which genetic variants potentially increase an individual's risk for developing PTSD. © 2016 Wiley Periodicals, Inc.

Neanderthal-Derived Genetic Variation Shapes Modern Human Cranium and Brain.

Before their disappearance from the fossil record approximately 40,000 years ago, Neanderthals, the ancient hominin lineage most closely related to modern humans, interbred with ancestors of present-day humans. The legacy of this gene flow persists through Neanderthal-derived variants that survive in modern human DNA; however, the neural implications of this inheritance are uncertain. Here, using MRI in a large cohort of healthy individuals of European-descent, we show that the amount of Neanderthal-originating polymorphism carried in living humans is related to cranial and brain morphology. First, as a validation of our approach, we demonstrate that a greater load of Neanderthal-derived genetic variants (higher "NeanderScore") is associated with skull shapes resembling those of known Neanderthal cranial remains, particularly in occipital and parietal bones. Next, we demonstrate convergent NeanderScore-related findings in the brain (measured by gray- and white-matter volume, sulcal depth, and gyrification index) that localize to the visual cortex and intraparietal sulcus. This work provides insights into ancestral human neurobiology and suggests that Neanderthal-derived genetic variation is neurologically functional in the contemporary population.

Late-Onset Alzheimer's Disease Polygenic Risk Profile Score Predicts Hippocampal Function.

BACKGROUND: We explored the cumulative effect of several late-onset Alzheimer's disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry. METHODS: In a sample of 231 healthy control subjects (19-55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level-dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects. RESULTS: There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested. CONCLUSIONS: There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes.

Regional Variations in Brain Gyrification Are Associated with General Cognitive Ability in Humans.

Searching for a neurobiological understanding of human intellectual capabilities has long occupied those very capabilities. Brain gyrification, or folding of the cortex, is as highly evolved and variable a characteristic in humans as is intelligence. Indeed, gyrification scales with brain size, and relationships between brain size and intelligence have been demonstrated in humans [1-3]. However, gyrification shows a large degree of variability that is independent from brain size [4-6], suggesting that the former may independently contribute to cognitive abilities and thus supporting a direct investigation of this parameter in the context of intelligence. Moreover, uncovering the regional pattern of such an association could offer insights into evolutionary and neural mechanisms. We tested for this brain-behavior relationship in two separate, independently collected, large cohorts-440 healthy adults and 662 healthy children-using high-resolution structural neuroimaging and comprehensive neuropsychometric batteries. In both samples, general cognitive ability was significantly associated (pFDR < 0.01) with increasing gyrification in a network of neocortical regions, including large portions of the prefrontal cortex, inferior parietal lobule, and temporoparietal junction, as well as the insula, cingulate cortex, and fusiform gyrus, a regional distribution that was nearly identical in both samples (Dice similarity coefficient = 0.80). This neuroanatomical pattern is consistent with an existing, well-known proposal, the Parieto-Frontal Integration Theory of intelligence [7], and is also consistent with research in comparative evolutionary biology showing rapid neocortical expansion of these regions in humans relative to other species. These data provide a framework for understanding the neurobiology of human cognitive abilities and suggest a potential neurocellular association.

Seeking Optimal Region-Of-Interest (ROI) Single-Value Summary Measures for fMRI Studies in Imaging Genetics.

A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others.

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

A variable number of tandem repeats in the 3'-untranslated region of the dopamine transporter modulates striatal function during working memory updating across the adult age span.

Dopamine modulation of striatal function is critical for executive functions such as working memory (WM) updating. The dopamine transporter (DAT) regulates striatal dopamine signaling via synaptic reuptake. A variable number of tandem repeats in the 3'-untranslated region of SLC6A3 (DAT1-3'-UTR-VNTR) is associated with DAT expression, such that 9-repeat allele carriers tend to express lower levels (associated with higher extracellular dopamine concentrations) than 10-repeat homozygotes. Aging is also associated with decline of the dopamine system. The goal of the present study was to investigate the effects of aging and DAT1-3'-UTR-VNTR on the neural activity and functional connectivity of the striatum during WM updating. Our results showed both an age-related decrease in striatal activity and an effect of DAT1-3'-UTR-VNTR. Ten-repeat homozygotes showed reduced striatal activity and increased striatal-hippocampal connectivity during WM updating relative to the 9-repeat carriers. There was no age by DAT1-3'-UTR-VNTR interaction. These results suggest that, whereas striatal function during WM updating is modulated by both age and genetically determined DAT levels, the rate of the age-related decline in striatal function is similar across both DAT1-3'-UTR-VNTR genotype groups. They further suggest that, because of the baseline difference in striatal function based on DAT1-3'-UTR-VNTR polymorphism, 10-repeat homozygotes, who have lower levels of striatal function throughout the adult life span, may reach a threshold of decreased striatal function and manifest impairments in cognitive processes mediated by the striatum earlier in life than the 9-repeat carriers. Our data suggest that age and DAT1-3'-UTR-VNTR polymorphism independently modulate striatal function.

Altered hippocampal-parahippocampal function during stimulus encoding: a potential indicator of genetic liability for schizophrenia.

IMPORTANCE: Declarative memory-the ability to learn, store, and retrieve information-has been consistently reported to be altered in schizophrenia, and hippocampal-parahippocampal dysfunction has been implicated in this deficit. To elucidate the possible role of genetic risk factors in such findings, it is necessary to study healthy relatives of patients with schizophrenia who carry risk-associated genes but not the confounding factors related to the disorder. OBJECTIVE: To investigate whether altered brain responses, particularly in the hippocampus and parahippocampus, during the encoding phase of a simple declarative memory task are also observed in unaffected siblings who are at increased genetic risk for schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Functional magnetic resonance imaging was used with a simple visual declarative memory paradigm to test for differences in neural activation across normal control participants, patients with schizophrenia, and their healthy siblings. This study was conducted at a research center and included a total of 308 participants (181 normal control participants, 65 healthy siblings, and 62 patients with schizophrenia); all participants were white of European ancestry. MAIN OUTCOMES AND MEASURES: All participants completed a declarative memory task involving incidental encoding of neutral visual scenes interleaved with crosshair fixation while undergoing functional magnetic resonance imaging. Differences in hippocampus and parahippocampus activation and coupling across groups and correlations with accuracy were analyzed. Analyses were repeated in pairwise-matched samples. RESULTS: Both patients with schizophrenia and their healthy siblings showed reduced parahippocampal activation (bilaterally) and hippocampal-parietal (BA 40) coupling during the encoding of novel stimuli when compared with normal control participants. There was a significant positive correlation between parahippocampal activation during encoding and the visual-memory score. CONCLUSIONS AND RELEVANCE: These results suggest that altered hippocampal-parahippocampal function during encoding is an intermediate biologic phenotype related to increased genetic risk for schizophrenia. Therefore, measuring hippocampal-parahippocampal function with neuroimaging represents a potentially useful approach to understanding genetic mechanisms that confer risk for schizophrenia.