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Background Negative symptoms such as blunted facial expressivity are characteristic of schizophrenia. However, it is not well-understood if and what abnormalities are present in individuals at clinical high-risk (CHR) for psychosis. Methods This experimental study employed facial electromyography (left zygomaticus major and left corrugator supercilia) in a sample of CHR individuals (N = 34) and healthy controls (N = 32) to detect alterations in facial expressions in response to emotionally evocative film clips and to determine links with symptoms. Results Findings revealed that the CHR group showed facial blunting manifested in reduced zygomatic activity in response to an excitement (but not amusement, fear, or sadness) film clip compared to controls. Reductions in zygomatic activity in the CHR group emerged in response to the emotionally evocative peak period of the excitement film clip. Lower zygomaticus activity during the excitement clip was related to anxiety while lower rates of change in zygomatic activity during the excitement video clip were related to higher psychosis risk conversion scores. Conclusions Together, these findings inform vulnerability/disease driving mechanisms and biomarker and treatment development.

Anatomical organization of the primate cortex varies as a function of total brain size, where possession of a larger brain is accompanied by disproportionate expansion of associative cortices alongside a relative contraction of sensorimotor systems. However, equivalent scaling maps are not yet available for regional white matter anatomy. Here, we use three large-scale neuroimaging datasets to examine how regional white matter volume (WMV) scales with interindividual variation in brain volume among typically developing humans (combined N = 2391: 1247 females, 1144 males). We show that WMV scaling is regionally heterogeneous: larger brains have relatively greater WMV in anterior and posterior regions of cortical white matter, as well as the genu and splenium of the corpus callosum, but relatively less WMV in most subcortical regions. Furthermore, regions of positive WMV scaling tend to connect previously-defined regions of positive gray matter scaling in the cortex, revealing a coordinated coupling of regional gray and white matter organization with naturally occurring variations in human brain size. However, we also show that two commonly studied measures of white matter microstructure, fractional anisotropy (FA) and magnetization transfer (MT), scale negatively with brain size, and do so in a manner that is spatially unlike WMV scaling. Collectively, these findings provide a more complete view of anatomic scaling in the human brain, and offer new contexts for the interpretation of regional white matter variation in health and disease. SIGNIFICANCE STATEMENT Recent work has shown that, in humans, regional cortical and subcortical anatomy show systematic changes as a function of brain size variation. Here, we show that regional white matter structures also show brain-size related changes in humans. Specifically, white matter regions connecting higher-order cortical systems are relatively expanded in larger human brains, while subcortical and cerebellar white matter tracts responsible for unimodal sensory or motor functions are relatively contracted. This regional scaling of white matter volume (WMV) is coordinated with regional scaling of cortical anatomy, but is distinct from scaling of white matter microstructure. These findings provide a more complete view of anatomic scaling of the human brain, with relevance for evolutionary, basic, and clinical neuroscience.

Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have discovered thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes1–3. However, rare-variant genetic architecture is not well characterized, and the relationship between common- and rare-variant architecture is unclear4. Here, we quantify the heritability explained by gene-wise burden of rare coding variants and compare the genetic architecture of common and rare variation across 22 common traits and diseases in 400,000 UK Biobank exomes5. Rare coding variants (AF = 1e-6 - 1e-3) explain 1.3% (SE = 0.03%) of phenotypic variance on average – much less than common variants – and most burden heritability is explained by ultra-rare loss-of-function variants (AF = 1e-6 - 1e-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in a limited number of significant genes (median: 6 genes explaining 19% of h2), while common-variant heritability is much more polygenic. Burden heritability is also more strongly concentrated in constrained genes (median enrichment: 4.5x vs. 2.1x for common variants), indicating that negative selection affects common- and rare-variant architecture differently. Finally, we find that burden heritability for schizophrenia and bipolar disorder6,7 is approximately 2%. Our results show that there are a tractable number of large-effect genes to discover by studying rare variants, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.

Klinefelter syndrome (47, XXY; Henceforth: XXY syndrome) is a high impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first neuroimaging study to map resting-state functional connectivity (rsFC) changes in XXY syndrome and ask how these might relate to brain anatomy and psychopathology. We collected resting state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males. We implemented a brain-wide screen to identify regions with altered global rsFC in XXY vs. XY males, and then used seed-based analysis to decompose these alterations. We further compared rsFC changes with regional changes in brain volume from voxel-based morphometry and tested for correlations between rsFC and symptom variation within XXY syndrome. We found that XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC), associated with overconnectivity with diverse rsFC networks. Regional rsFC changes were partly coupled to regional volumetric changes in XXY syndrome. Within the precuneus, variation in DLPFC rsFC within XXY syndrome was correlated with the severity of psychopathology in XXY individuals. Our findings provide the first view of altered functional brain connectivity in XXY syndrome and delineate links between these alterations and those relating to both brain anatomy and psychopathology. Taken together, these insights advance biological understanding of XXY syndrome as a disorder in its own right, and as a model of genetic risk for psychopathology more broadly.

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Emotions broaden or narrow the scope of attention in order to facilitate adaptive responses in threatening and rewarding contexts. In the current study, rather than asking how emotions influence attentional scope, we considered the possibility that the relationship between attentional breadth and emotion is bidirectional by asking whether shifts in attentional scope alter emotional processes using an event-related potential (ERP) paradigm. Participants (N = 30) completed a modified version of a Monetary Incentive Delay (MID) task, wherein their attention was either narrowed or broadened as they attempted to win rewards. Behaviorally, narrowing attention improved task performance in the form of reduced errors and increased monetary winnings. During cue processing, narrowing (compared to broadening) attention reduced the Cue-P3 (irrespective of cue type). During feedback processing, narrowing (compared to broadening) attention reduced the Feedback-P3 to monetary wins and increased the Feedback-P2 and the Feedback-P3 to monetary non-wins. Results highlight complexity and bidirectionality in the relationship between attentional scope and affective processes.

Brain structural covariance norms capture the coordination of neurodevelopmental programs between different brain regions. We develop and apply anatomical imbalance mapping (AIM), a method to measure and model individual deviations from these norms, to provide a lifespan map of morphological integration in the human cortex. In cross-sectional and longitudinal data, analysis of whole-brain average anatomical imbalance reveals a reproducible tightening of structural covariance by age 25 y, which loosens after the seventh decade of life. Anatomical imbalance change in development and in aging is greatest in the association cortex and least in the sensorimotor cortex. Finally, we show that interindividual variation in whole-brain average anatomical imbalance is positively correlated with a marker of human prenatal stress (birthweight disparity between monozygotic twins) and negatively correlated with general cognitive ability. This work provides methods and empirical insights to advance our understanding of coordinated anatomical organization of the human brain and its interindividual variation.

Neurodevelopmental disorders have a heritable component and are associated with region specific alterations in brain anatomy. However, it is unclear how genetic risks for neurodevelopmental disorders are translated into spatially patterned brain vulnerabilities. Here, we integrated cortical neuroimaging data from patients with neurodevelopmental disorders caused by genomic copy number variations (CNVs) and gene expression data from healthy subjects. For each of the six investigated disorders, we show that spatial patterns of cortical anatomy changes in youth are correlated with cortical spatial expression of CNV genes in neurotypical adults. By transforming normative bulk-tissue cortical expression data into cell-type expression maps, we link anatomical change maps in each analysed disorder to specific cell classes as well as the CNV-region genes they express. Our findings reveal organizing principles that regulate the mapping of genetic risks onto regional brain changes in neurogenetic disorders. Our findings will enable screening for candidate molecular mechanisms from readily available neuroimaging data.

Neurodevelopmental disorders have a heritable component and are associated with region specific alterations in brain anatomy. However, it is unclear how genetic risks for neurodevelopmental disorders are translated into spatially patterned brain vulnerabilities. Here, we integrated cortical neuroimaging data from patients with neurodevelopmental disorders caused by genomic copy number variations (CNVs) and gene expression data from healthy subjects. For each of the six investigated disorders, we show that spatial patterns of cortical anatomy changes in youth are correlated with cortical spatial expression of CNV genes in neurotypical adults. By transforming normative bulk-tissue cortical expression data into cell-type expression maps, we link anatomical change maps in each analysed disorder to specific cell classes as well as the CNV-region genes they express. Our findings reveal organizing principles that regulate the mapping of genetic risks onto regional brain changes in neurogenetic disorders. Our findings will enable screening for candidate molecular mechanisms from readily available neuroimaging data., How neurodevelopmental disorder-associated risk genes are translated into spatially patterned brain vulnerabilities is unclear. Here, the authors show that disorder-specific patterns of neuroanatomical changes are aligned to brain expression maps of disease risk genes in healthy subjects.

Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i)in vivoneuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorder’s anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this “transcriptional vulnerability model” by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and blood-derived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with human structural brain development is not yet well characterized. Here, we analyzed 1243 longitudinally acquired structural MRI scans from 623 youth (299 female/324 male) to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were stable between ages 5 and 25. Surface-based shape analysis revealed that higher SES is associated with areal expansion of lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and ventrolateral thalamic, and medial amygdalo-hippocampal subregions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Although SES is clearly a complex construct that likely relates to development through diverse, nondeterministic processes, our findings elucidate potential neuroanatomical mediators of the association between SES and cognitive outcomes.SIGNIFICANCE STATEMENTChildhood socioeconomic status (SES) has been associated with developmental disparities in mental health, cognitive ability, and academic achievement, but efforts to understand underlying SES–brain relationships are ongoing. Here, we leverage a unique developmental neuroimaging dataset to longitudinally map the associations between SES and regional brain anatomy at high spatiotemporal resolution. We find widespread associations between SES and global cortical and subcortical volumes and surface area and localize these correlations to a distributed set of cortical, thalamic, and amygdalo-hippocampal subregions. Anatomical variation within a subset of these regions partially mediates the positive relationship between SES and IQ. Our findings help to localize cortical and subcortical systems that represent candidate biological substrates for the known relationships between SES and cognition.

Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with structural brain development is not yet well-characterized. Here, we analyzed 1243 longitudinally-acquired structural MRI scans from 623 youth to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were developmentally fixed rather than age-dependent. Surface-based shape analysis revealed that higher SES is associated with areal expansion of (i) lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and (ii) ventrolateral thalamic, and medial amygdalo-hippocampal sub-regions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Our findings clarify the spatiotemporal patterning of SES-related neuroanatomical variation and inform ongoing efforts to dissect the causal pathways underpinning observed associations between childhood SES and regional brain anatomy.

Sex chromosome aneuploidy (SCA) enhances risk for several psychiatric disorders associated with the limbic system, including mood and autism spectrum disorders. These patients provide a powerful genetics-first model for understanding the biological basis of psychopathology. Additionally, these disorders are frequently sex-biased in prevalence, further suggesting an etiological role for sex chromosomes. To clarify how limbic anatomy varies across sex and sex chromosome complement, we characterized amygdala and hippocampus structure in a uniquely large sample of patients carrying supernumerary sex chromosomes (n = 132) and typically developing controls (n=166). After correction for sex-differences in brain size, karyotypically normal males (XY) and females (XX) did not differ in volume or shape of either structure. In contrast, all SCAs were associated with lowered amygdala volume relative to gonadally-matched controls. This effect was robust to three different methods for total brain volume correction, including an allometric analysis that derived normative scaling rules for these structures in a separate, typically developing population (n = 79). Hippocampal volume was insensitive to SCA after correction for total brain volume. However, surface-based analysis revealed that SCA, regardless of specific karyotype, was consistently associated with a spatially specific pattern of shape change in both amygdala and hippocampus. In particular, SCA was accompanied by contraction around the basomedial nucleus of the amygdala and an area within the hippocampal surface that cuts across hippocampal subfields. These results demonstrate the power of SCA as a model to understand how copy number variation can precipitate changes in brain systems relevant to psychiatric disease.

Perhaps you’re working in a laboratory at your college or traveling to a new institution in a far flung location. In either case, a research internship can be an incredible stepping stone in your professional, intellectual, and personal development. Over the summer, you can learn cutting edge techniques, expand your network, and refine your interests as you look towards graduate school or the job market. The process of obtaining a summer internship can be as long and subjective as applying for or choosing an undergraduate institution. Summer research programs are increasingly competitive—some such as Amgen programs have 1,000 to 2,000 applicants for just 2 dozen spots. The strategies and specifics of acquiring a summer research internship could be a “Ten simple rules” post of its own, so we point readers to articles and tools that have explored this topic previously (S1 Table). Keep in mind that you don't have to be at a prestigious institution to learn new techniques, gain exposure to a new research field, and connect with scientists and other scientists-in-training. Guidelines have been presented in this article series on how to approach undergraduate research in general [1]. Building on these helpful rules, we observe that summer research internships present unique challenges due to their immersive and time-limited nature. That being said, these short-term positions present a unique set of challenges that may prevent interns from getting the most out of the summer months. For instance, research projects often operate on the timescale of years, leaving it unclear how to best spend an 8 to 10 week internship. With busy summer schedules and unclear expectations, interns may end up completing laboratory procedures without intellectually engaging in their project. To help interns and mentors navigate these and other related issues, we have compiled advice based on our collective 16 summer research experiences. We hope that these suggestions will help interns optimally learn from and contribute to their lab. More broadly, by sharing these tips, we hope more interns will experience the thrills of laboratory research that have led all of us to pursue careers in science. Rule 1: Plan ahead! Any project that you work on as an intern is probably part of an effort that spans multiple years. To have a meaningful internship experience, you need to have a small slice of that project that is both significant and doable in a short amount of time. It is not easy or obvious for your mentors to design a summer project that achieves both of these goals. Planning ahead with your mentor can help make sure the internship experience is productive and engaging. In general, mentors who take on undergraduate summer students want to create great projects, but busy schedules may hinder extensive planning. Postdocs and graduate students may learn that they are expected to advise a summer student with a week or two of notice, and must cobble together suitable projects. As soon as you are accepted to a summer internship, reach out to your PI to express (1) your excitement at working in the lab, (2) that you are eager to begin discussing your project with your direct supervisor, and (3) ask for reading material to gain background for further correspondence. Repeat these sentiments prior to your arrival as well, as a reminder of your upcoming presence. As you work through preliminary readings, connect back with your supervisor with sections that appealed to or challenged you. If you are able to successfully communicate in this way, supervisors can make subtle decisions in experimental animal allocation, surgery timing, and reagent ordering to facilitate a great summer project.

Although waiting for a reward reduces or discounts its value, some people have a stronger tendency to wait for larger rewards and forgo smaller-but-immediate rewards. This ability to delay gratification is captured by individual differences in so-called inter-temporal choices in which individuals are asked to choose between larger-but-delayed versus smaller-but-immediate rewards. The current study used event-related potentials (ERPs) to examine whether enhancement in two neuro-cognitive processes, outcome-anticipation and outcome-evaluation, modulate individual variability in inter-temporal responses. After completing a behavioral inter-temporal choice task, 34 participants performed an ERP gambling task. From this ERP task, we separately examined individual differences in outcome-anticipation (Stimulus-Preceding Negativity, SPN), early outcome-evaluation (Feedback-Related Negativity; FRN) and late outcome-evaluation (P3). We observed that both elevated outcome-anticipation (SPN) and late outcome-evaluation (P3) neural processes predicted a stronger preference toward larger-but-delayed rewards. No relationship was observed between inter-temporal responses and early outcome-evaluation (FRN), indicating that the relationship between outcome-evaluation and inter-temporal responses was specific to the late outcome-evaluation processing stream. Moreover, multiple regression analyses indicated that the SPN and P3 independently modulate individual differences in inter-temporal responses, suggesting separate mechanisms underlie the relationship between these two neuro-cognitive processes and inter-temporal responses. Accordingly, we identify two potential neural-cognitive modulators of individual variability in inter-temporal responses. We discuss the mechanisms underlying these modulators in terms of anticipation-related processing (SPN) and a saliency-bias toward gain (compared to loss) outcomes (P3).

The amygdala and hippocampus are two adjacent allocortical structures implicated in sex-biased and developmentally-emergent psychopathology. However, the spatiotemporal dynamics of amygdalo-hippocampal development remain poorly understood in healthy humans. The current study defined trajectories of volume and shape change for the amygdala and hippocampus by applying a multi-atlas segmentation pipeline (MAGeT-Brain) and semi-parametric mixed-effects spline modeling to 1,529 longitudinally-acquired structural MRI brain scans from a large, single-center cohort of 792 youth (403 males, 389 females) between the ages of 5 and 25 years old. We found that amygdala and hippocampus volumes both follow curvilinear and sexually dimorphic growth trajectories. These sex-biases were particularly striking in the amygdala: males showed a significantly later and slower adolescent deceleration in volume expansion (at age 20 years) than females (age 13 years). Shape analysis localized significant hot-spots of sex-biased anatomical development in sub-regional territories overlying rostral and caudal extremes of the CA1/2 in the hippocampus, and the centromedial nuclear group of the amygdala. In both sexes, principal components analysis revealed close integration of amygdala and hippocampus shape change along two main topographically-organized axes – low vs. high areal expansion, and early vs. late growth deceleration. These results bring greater resolution to our spatiotemporal understanding of amygdalo-hippocampal development in healthy males and females and discover focal sex-differences in the structural maturation of the brain components that may contribute to differences in behavior and psychopathology that emerge during adolescence.SIGNIFICANCE STATEMENTThe amygdala and hippocampus are implicated in several developmentally-dynamic and sex-biased psychiatric disorders, but the spatiotemporal organization and sex-biased patterning of amygdalo-hippocampal maturation remains unclear in humans. Here, by integrating new methods for analysis of longitudinal neuroimaging data, we resolve the developmental milestones and spatial gradients that organize human amygdalo-hippocampal maturation. Each structure’s volume follows a tri-phasic, curvilinear growth trajectory which - for the amygdala - shows rapid male-female size divergence in mid-adolescence through delayed growth deceleration in males. Spatially fine-grained shape analyses localize these sex differences, and further reveal highly orchestrated shape changes across the amygdala and hippocampus that are organized by two topographical gradients. These data provide a new framework for understanding amygdalo-hippocampal organization in human development.

Lupus is less common in men than women, and the reason is incompletely understood. Current evidence indicates that lupus flares when genetically predisposed individuals encounter environmental agents that trigger the disease, and that the environmental contribution is mediated at least in part by T cell DNA demethylation. We hypothesized that lupus disease activity is directly related to total genetic risk and inversely related to T cell DNA methylation levels in each patient. Since women are predisposed to lupus in part because of their second X chromosome, we also hypothesized that men would require a greater genetic risk, a greater degree of autosomal T cell DNA demethylation, or both, to achieve a lupus flare equal in severity to women. Genetic risk was determined by genotyping men and women with lupus across 32 confirmed lupus susceptibility loci. The methylation status of two autosomal genes known to demethylate in T cells in proportion to disease activity, KIR2DL4 (KIR) and PRF1, was measured by bisulfite sequencing. Lupus disease activity was determined by the SLEDAI. Interactions between genetic score, T cell DNA demethylation, and the SLEDAI score were compared between the men and women by regression analysis. Combining the degree of DNA demethylation with the genetic risk score for each patient demonstrated that the (genetic risk)/(DNA methylation) ratio increased directly with disease activity in both men and women with lupus. Importantly, men required a greater (genetic risk)/(DNA methylation) ratio to achieve a SLEDAI score equivalent to women (P = 0.010 for KIR and P = 0.0054 for PRF1). This difference was not explained by a difference in the genetic risk or T cell DNA demethylation alone, suggesting a genetic-epigenetic interaction. These results suggest that genetic risk and T cell DNA demethylation interact in lupus patients to influence the severity of lupus flares, and that men require a higher genetic risk and/or greater degree of T cell DNA demethylation to achieve a lupus flare equal in severity to women.

ObjectiveSystemic lupus erythematosus is a clinically heterogeneous autoimmune disease. A number of genetic loci that increase lupus susceptibility have been established. This study examines if these genetic loci also contribute to the clinical heterogeneity in lupus.Materials and methods4001 European-derived, 1547 Hispanic, 1590 African-American and 1191 Asian lupus patients were genotyped for 16 confirmed lupus susceptibility loci. Ancestry informative markers were genotyped to calculate and adjust for admixture. The association between the risk allele in each locus was determined and compared in patients with and without the various clinical manifestations included in the ACR criteria.ResultsRenal disorder was significantly correlated with the lupus risk allele in ITGAM (p=5.0×10−6, OR 1.25, 95% CI 1.12 to 1.35) and in TNFSF4 (p=0.0013, OR 1.14, 95% CI 1.07 to 1.25). Other significant findings include the association between risk alleles in FCGR2A and malar rash (p=0.0031, OR 1.11, 95% CI 1.17 to 1.33), ITGAM and discoid rash (p=0.0020, OR 1.20, 95% CI 1.06 to 1.33), STAT4 and protection from oral ulcers (p=0.0027, OR 0.89, 95% CI 0.83 to 0.96) and IL21 and haematological disorder (p=0.0027, OR 1.13, 95% CI 1.04 to 1.22). All these associations are significant with a false discovery rate of ConclusionSignifi cant associations were found between clinical manifestations and the FCGR2A, ITGAM, STAT4, TNSF4 and IL21 genes. The findings suggest that genetic profiling might be a useful tool to predict disease manifestations in lupus patients in the future.

To the Editor: Sanchez, et al have recently reported an association between a putative functional genetic variant in the promoter region of IL18 (rs360719) and systemic lupus erythematosus in Spanish patients1. They found an increase in the relative expression of IL18 mRNA in individuals with the rs360719 lupus-risk allele1. Interleukin 18 (IL-18) is a pleiotropic cytokine that can induce Th1 and Th2 responses in the presence and absence, respectively, of IL-122. Studies have described overproduction of IL-18 in several autoimmune and inflammatory diseases including Behcet’s disease (BD) and lupus3,4. Indeed, serum IL-18 levels in patients with lupus and BD correlate with disease activity5,6. We attempted to replicate the results of Sanchez, et al in a set of Turkish patients with lupus. We examined if the same putative functional IL18 polymorphism is associated with BD in … Address correspondence to Dr. A.H. Sawalha, 825 NE 13th Street, MS 24, Oklahoma City, OK 73104. E-mail: amr-sawalha{at}omrf.ouhsc.edu

WOS: 000297221100049, PubMed ID: 21918955, Objective. Using a genome-wide association scan and DNA pooling, we previously identified 5 novel genetic susceptibility loci for Behc,et's disease. We undertook this study to establish the genetic effect within the UBAC2 gene, in the course of which we replicated this genetic association and identified a functional variant within this locus. Methods. We studied a total of 676 Behcet's disease patients and 1,096 controls. The discovery set included 156 patients and 167 controls from Turkey, and the replication sets included 376 patients and 369 controls from Turkey and 144 patients and 560 controls from Italy. Genotyping of 14 single-nucleotide polymorphisms (SNPs) within and around UBAC2 was performed using TaqMan SNP genotyping assays. Results. The genetic association between Behc, et's disease and UBAC2 was established, replicated, and confirmed (meta-analysis odds ratio 1.84, P = 1.69 x 10(-7)). Haplotype analysis identified both a disease-risk haplotype and a protective haplotype (P = 0.00014 and P = 0.0075, respectively). Using conditional haplotype analysis, we identified the SNP rs7999348 (A/G) within UBAC2 as the most likely SNP with a genetic effect independent of the haplotypic effect formed by the remaining associated SNPs in this locus. Indeed, we demonstrated that rs7999348 tags a functional variant associated with increased messenger RNA expression of a UBAC2 transcript variant in peripheral blood mononuclear cells of individuals homozygous for the Behc, et's disease-associated "G" allele. Further, our data suggested the possibility of multiple genetic effects that increase susceptibility to Behc, et's disease in the UBAC2 locus. Conclusion. We established and confirmed the genetic association between UBAC2 and Behcet's disease in 3 independent sets of patients and controls. We identified the minor allele in rs7999348 as a disease-risk allele that tags altered UBAC2 expression., American College of Rheumatology Research and Education Foundation; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R03-AI-076729, P20-RR-020143, P30-AR-053483], Supported by the American College of Rheumatology Research and Education Foundation (Rheumatology Investigator Award to Dr. Sawalha) and by the NIH (grants R03-AI-076729, P20-RR-020143, and P30-AR-053483).