The genetic dissection of fetal haemoglobin persistence in sickle cell disease in Nigeria.

The clinical severity of sickle cell disease (SCD) is strongly influenced by the level of fetal haemoglobin (HbF) persistent in each patient. Three major HbF loci (BCL11A, HBS1L-MYB, and Xmn1-HBG2) have been reported, but a considerable hidden heritability remains. We conducted a genome-wide association study for HbF levels in 1006 Nigerian patients with SCD (HbSS/HbSß0), followed by a replication and meta-analysis exercise in four independent SCD cohorts (3,582 patients). To dissect association signals at the major loci, we performed stepwise conditional and haplotype association analyses and included public functional annotation datasets. Association signals were detected for BCL11A (lead SNP rs6706648, ß = -0.39, P = 4.96 × 10-34) and HBS1L-MYB (lead SNP rs61028892, ß = 0.73, P = 1.18 × 10-9), whereas the variant allele for Xmn1-HBG2 was found to be very rare. In addition, we detected three putative new trait-associated regions. Genetically, dissecting the two major loci BCL11A and HBS1L-MYB, we defined trait-increasing haplotypes (P < 0.0001) containing so far unidentified causal variants. At BCL11A, in addition to a haplotype harbouring the putative functional variant rs1427407-'T', we identified a second haplotype, tagged by the rs7565301-'A' allele, where a yet-to-be-discovered causal DNA variant may reside. Similarly, at HBS1L-MYB, one HbF-increasing haplotype contains the likely functional small indel rs66650371, and a second tagged by rs61028892-'C' is likely to harbour a presently unknown functional allele. Together, variants at BCL11A and HBS1L-MYB SNPs explained 24.1% of the trait variance. Our findings provide a path for further investigation of the causes of variable fetal haemoglobin persistence in sickle cell disease.

Crustacean cardioactive peptide signaling system in the gastropod mollusk Pacific abalone.

Crustacean cardioactive peptide (CCAP) signaling systems have been characterized in a diverse range of protostomes, representatively in arthropods. The cyclic CX5C-type CCAP regulates various biological activities through CCAP receptors (CCAPRs), which are orthologous to neuropeptide S receptors (NPSRs) in deuterostomes. However, the CCAPRs of the lophotrochozoa remain poorly characterized; therefore, the relationship between the CCAP, NPS, and CX4C-type oxytocin/vasopressin (OT/VP) signaling systems is unclear. In this study, we identified a CCAP precursor and two CCAPR isoforms in the Pacific abalone (Haliotis discus hannai; Hdh). The Hdh-CCAP precursor was found to harbor three CX5C-type and one CX4C-type CCAPs. The Hdh-CCAPRs displayed homology with protostome CCAPRs and deuterostome NPSRs, having characteristics of the rhodopsin-type G protein-coupled receptors. Phylogenetic analysis showed that lophotrochozoan CCAPRs, including Hdh-CCAPRs, form a monophyletic group distinct from arthropod CCAPRs. Reporter assays demonstrated that all examined Hdh-CCAPs and insect CCAP-induced intracellular Ca2+ mobilization and cAMP accumulation in Hdh-CCAPR-expressing HEK293 cells, whereas none of the CCAP peptides inhibited the forskolin-stimulated cAMP signaling pathway even at micromolar concentrations. In silico ligand-receptor docking models showed that the N-terminal FCN motifs of Hdh-CCAPs are deeply inserted inside the binding pocket of Hdh-CCAPR, forming extensive hydrophobic interactions. In mature Pacific abalone, the transcripts for Hdh-CCAP precursor and Hdh-CCAPR were highly expressed in the neural ganglia compared to the peripheral tissues. Collectively, this study characterized the first CCAP signaling system linked to both Ca2+/PKC and cAMP/PKA signal transduction pathways in gastropod mollusks and gives insights into the evolutional origins of deuterostomian NPS and OT/VP signaling systems.

GWAS meta-analysis of psoriasis identifies new susceptibility alleles impacting disease mechanisms and therapeutic targets.

Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To move towards a saturation map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 45 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.

The United Kingdom Eating Disorders Genetics Initiative.

OBJECTIVE: The United Kingdom Eating Disorders Genetics Initiative (EDGI UK), part of the National Institute for Health and Care Research (NIHR) Mental Health BioResource, aims to deepen our understanding of the environmental and genetic etiology of eating disorders. EDGI UK launched in February 2020 and is partnered with the UK eating disorders charity, Beat. Multiple EDGI branches exist worldwide. This article serves the dual function of providing an in-depth description of our study protocol and of describing our initial sample including demographics, diagnoses, and physical and psychiatric comorbidities. METHOD: EDGI UK recruits via media and clinical services. Anyone living in England, at least 16 years old, with a lifetime probable or clinical eating disorder is eligible to sign up online: edgiuk.org. Participants complete online questionnaires, donate a saliva sample for genetic analysis, and consent to medical record linkage and recontact for future studies. RESULTS: As of September 2022, EDGI UK recruited 7435 survey participants: 98% female, 93.1% white, 97.8% cisgender, 65.9% heterosexual, and 52.1% have a university degree. Over half (57.8%) of these participants have returned their saliva DNA kit. The most common diagnoses are anorexia nervosa (48.3%), purging disorder (37.8%), bulimia nervosa (37.5%), binge-eating disorder (15.8%), and atypical anorexia nervosa (7.8%). CONCLUSION: EDGI UK is the largest UK eating disorders study and efforts to increase its diversity are underway. It offers a unique opportunity to accelerate eating disorder research. Researchers and participants with lived experience can collaborate on projects with unparalleled sample size. PUBLIC SIGNIFICANCE STATEMENT: Eating disorders are debilitating and costly for society but are under-researched due to underfunding. EDGI UK is one of the largest eating disorder studies worldwide with ongoing recruitment. The collected data constitute a resource for secondary analysis. We will combine data from all international EDGI branches and the NIHR BioResource to facilitate research that improves our understanding of eating disorders and their comorbidities.

Genetic examination of the Mood Disorder Questionnaire and its relationship with bipolar disorder.

The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (N = 11,568-19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (rg = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (rp = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (rg = 0.69), insomnia (rg = 0.55), and major depressive disorder (rg = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.

Factors associated with anxiety disorder comorbidity.

BACKGROUND: Anxiety and depressive disorders often co-occur and the order of their emergence may be associated with different clinical outcomes. However, minimal research has been conducted on anxiety-anxiety comorbidity. This study examined factors associated with anxiety comorbidity and anxiety-MDD temporal sequence. METHODS: Online, self-report data were collected from the UK-based GLAD and COPING NBR cohorts (N = 38,775). Logistic regression analyses compared differences in sociodemographic, trauma, and clinical factors between single anxiety, anxiety-anxiety comorbidity, anxiety-MDD (major depressive disorder) comorbidity, and MDD-only. Additionally, anxiety-first and MDD-first anxiety-MDD were compared. Differences in familial risk were assessed in those participants with self-reported family history or genotype data. RESULTS: Anxiety-anxiety and anxiety-MDD had higher rates of self-reported anxiety or depressive disorder diagnoses, younger age of onset, and higher recurrence than single anxiety. Anxiety-MDD displayed greater clinical severity/complexity than MDD only. Anxiety-anxiety had more severe current anxiety symptoms, less severe current depressive symptoms, and reduced likelihood of self-reporting an anxiety/depressive disorder diagnosis than anxiety-MDD. Anxiety-first anxiety-MDD had a younger age of onset, more severe anxiety symptoms, and less likelihood of self-reporting a diagnosis than MDD-first. Minimal differences in familial risk were found. LIMITATIONS: Self-report, retrospective measures may introduce recall bias. The familial risk analyses were likely underpowered. CONCLUSIONS: Anxiety-anxiety comorbidity displayed a similarly severe and complex profile of symptoms as anxiety-MDD but distinct features. For anxiety-MDD, first-onset anxiety had an earlier age of onset and greater severity than MDD-first. Anxiety disorders and comorbidity warrant further investigation and attention in research and practice.

10-mer and 9-mer WALK Peptides with Both Antibacterial and Anti-Inflammatory Activities.

Natural antimicrobial peptides (AMPs) are multifunctional host defense peptides (HDPs) that are valuable for various therapeutic applications. In particular, natural and artificial AMPs with dual antibacterial immunomodulatory functions emerged as promising candidates for the development of therapeutic agents to treat infectious inflammation. In an effort to develop useful AMP variants with short lengths and simple amino acid composition, we devised a de novo design strategy to generate a series of model peptide isomer sequences, named WALK peptides, i.e., tryptophan (W)-containing amphipathic-helical (A) leucine (L)/lysine (K) peptides. Here, we generated two groups of WALK peptide isomers: W2L4K4 (WALK244.01~WALK244.10) and W2L4K3 (WALK243.01~WALK243.09). Most showed apparent antibacterial activities against both Gram-positive and Gram-negative bacteria at a concentration of approximately 4 µg/mL along with varied hemolytic activities against human red blood cells. In addition, some exhibited significant anti-inflammatory activities without any significant cytotoxicity in macrophages. Collectively, these results suggest that the two selected peptides, WALK244.04 and WALK243.04, showed promise for the development of antibacterial and anti-inflammatory agents.

The COPILOT Raw Illumina Genotyping QC Protocol.

The Illumina genotyping microarrays generate data in image format, which is processed by the platform-specific software GenomeStudio, followed by an array of complex bioinformatics analyses that rely on various software, different programming languages, and numerous dependencies to be installed and configured correctly. The entire process can be time-consuming, can lead to reproducibility errors, and can be a daunting task for bioinformaticians. To address this, we introduce the COPILOT protocol, which has been successfully used to transform raw Illumina genotype intensity data into high-quality analysis-ready data on tens of thousands of human patient samples that have been genotyped on a variety of Illumina genotyping arrays. This includes processing both mainstream and custom content genotyping chips with over 4 million markers per sample. The COPILOT QC protocol consists of two distinct tandem procedures to process raw Illumina genotyping data. The first protocol is an up-to-date process to systematically QC raw Illumina microarray genotyping data using the Illumina-specific GenomeStudio software. The second protocol takes the output from the first protocol and further processes the data through the COPILOT (Containerised wOrkflow for Processing ILlumina genOtyping daTa) containerized QC pipeline, to automate an array of complex bioinformatics analyses to improve data quality through a secondary clustering algorithm and to automatically identify typical Genome-Wide Association Study (GWAS) data issues, including gender discrepancies, heterozygosity outliers, related individuals, and population outliers, through ancestry estimation. The data is returned to the user in analysis-ready PLINK binary format and is accompanied by a comprehensive and interactive HTML summary report file which quickly helps the user understand the data and guides the user for further data analyses. The COPILOT protocol and containerized pipeline are also available at https://khp-informatics.github.io/COPILOT/index.html. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing raw Illumina genotyping data using GenomeStudio Basic Protocol 2: COPILOT: A containerised workflow for processing Illumina genotyping data.

Differences in Clinical Features and Comorbid Burden between HLA-C∗06:02 Carrier Groups in >9,000 People with Psoriasis.

The identification of robust endotypes-disease subgroups of clinical relevance-is fundamental to stratified medicine. We hypothesized that HLA-C∗06:02 status, the major genetic determinant of psoriasis, defines a psoriasis endotype of clinical relevance. Using two United Kingdom-based cross-sectional datasets-an observational severe-psoriasis study (Biomarkers of Systemic Treatment Outcomes in Psoriasis; n = 3,767) and a large population-based bioresource (UK Biobank, including n = 5,519 individuals with psoriasis)-we compared demographic, environmental, and clinical variables of interest in HLA-C∗06:02-positive (one or two copies of the HLA-C∗06:02 allele) with those in HLA-C∗06:02‒negative (no copies) individuals of European ancestry. We used multivariable regression analyses to account for mediation effects established a priori. We confirm previous observations that HLA-C∗06:02-positive status is associated with earlier age of psoriasis onset and extend findings to reveal an association with disease expressivity in females (Biomarkers of Systemic Treatment Outcomes in Psoriasis: P = 2.7 × 10-14, UK Biobank: P = 1.0 × 10-8). We also show HLA-C∗06:02-negative status to be associated with characteristic clinical features (large plaque disease, OR for HLA-C∗06:02 = 0.73, P = 7.4 × 10-4; nail involvement, OR = 0.70, P = 2.4 × 10-6); higher central adiposity (Biomarkers of Systemic Treatment Outcomes in Psoriasis: waist circumference difference of 2.0 cm, P = 8.4 × 10-4; UK Biobank: waist circumference difference of 1.4 cm, P = 1.5 × 10-4), especially in women; and a higher prevalence of other cardiometabolic comorbidities. These findings extend the clinical phenotype delineated by HLA-C∗06:02 and highlight its potential as an important biomarker to consider in future multimarker stratified medicine approaches.

Transcriptomic analysis of probable asymptomatic and symptomatic alzheimer brains.

Individuals with intact cognition and neuropathology consistent with Alzheimer's disease (AD) are referred to as asymptomatic AD (AsymAD). These individuals are highly likely to develop AD, yet transcriptomic changes in the brain which might reveal mechanisms for their AD vulnerability are currently unknown. Entorhinal cortex, frontal cortex, temporal cortex and cerebellum tissue from 27 control, 33 AsymAD and 52 AD human brains were microarray expression profiled. Differential expression analysis identified a significant increase of transcriptomic activity in the frontal cortex of AsymAD subjects, suggesting fundamental changes in AD may initially begin within the frontal cortex region prior to AD diagnosis. Co-expression analysis identified an overactivation of the brain "glutamate-glutamine cycle", and disturbances in the brain energy pathways in both AsymAD and AD subjects, while the connectivity of key hub genes in this network indicates a shift from an already increased cell proliferation in AsymAD subjects to stress response and removal of amyloidogenic proteins in AD subjects. This study provides new insight into the earliest biological changes occurring in the brain prior to the manifestation of clinical AD symptoms and provides new potential therapeutic targets for early disease intervention.

A genome-wide association meta-analysis of prognostic outcomes following cognitive behavioural therapy in individuals with anxiety and depressive disorders.

Major depressive disorder and the anxiety disorders are highly prevalent, disabling and moderately heritable. Depression and anxiety are also highly comorbid and have a strong genetic correlation (rg ≈ 1). Cognitive behavioural therapy is a leading evidence-based treatment but has variable outcomes. Currently, there are no strong predictors of outcome. Therapygenetics research aims to identify genetic predictors of prognosis following therapy. We performed genome-wide association meta-analyses of symptoms following cognitive behavioural therapy in adults with anxiety disorders (n = 972), adults with major depressive disorder (n = 832) and children with anxiety disorders (n = 920; meta-analysis n = 2724). We estimated the variance in therapy outcomes that could be explained by common genetic variants (h2SNP) and polygenic scoring was used to examine genetic associations between therapy outcomes and psychopathology, personality and learning. No single nucleotide polymorphisms were strongly associated with treatment outcomes. No significant estimate of h2SNP could be obtained, suggesting the heritability of therapy outcome is smaller than our analysis was powered to detect. Polygenic scoring failed to detect genetic overlap between therapy outcome and psychopathology, personality or learning. This study is the largest therapygenetics study to date. Results are consistent with previous, similarly powered genome-wide association studies of complex traits.

Differential gene expression analysis in blood of first episode psychosis patients.

BACKGROUND: Psychosis is a condition influenced by an interaction of environmental and genetic factors. Gene expression studies can capture these interactions; however, studies are usually performed in patients who are in remission. This study uses blood of first episode psychosis patients, in order to characterise deregulated pathways associated with psychosis symptom dimensions. METHODS: Peripheral blood from 149 healthy controls and 131 first episode psychosis patients was profiled using Illumina HT-12 microarrays. A case/control differential expression analysis was performed, followed by correlation of gene expression with positive and negative syndrome scale (PANSS) scores. Enrichment analyses were performed on the associated gene lists. We test for pathway differences between first episode psychosis patients who qualify for a Schizophrenia diagnosis against those who do not. RESULTS: A total of 978 genes were differentially expressed and enriched for pathways associated to immune function and the mitochondria. Using PANSS scores we found that positive symptom severity was correlated with immune function, while negative symptoms correlated with mitochondrial pathways. CONCLUSIONS: Our results identified gene expression changes correlated with symptom severity and showed that key pathways are modulated by positive and negative symptom dimensions.

Genome-wide association study in frontal fibrosing alopecia identifies four susceptibility loci including HLA-B*07:02.

Frontal fibrosing alopecia (FFA) is a recently described inflammatory and scarring type of hair loss affecting almost exclusively women. Despite a dramatic recent increase in incidence the aetiopathogenesis of FFA remains unknown. We undertake genome-wide association studies in females from a UK cohort, comprising 844 cases and 3,760 controls, a Spanish cohort of 172 cases and 385 controls, and perform statistical meta-analysis. We observe genome-wide significant association with FFA at four genomic loci: 2p22.2, 6p21.1, 8q24.22 and 15q2.1. Within the 6p21.1 locus, fine-mapping indicates that the association is driven by the HLA-B*07:02 allele. At 2p22.1, we implicate a putative causal missense variant in CYP1B1, encoding the homonymous xenobiotic- and hormone-processing enzyme. Transcriptomic analysis of affected scalp tissue highlights overrepresentation of transcripts encoding components of innate and adaptive immune response pathways. These findings provide insight into disease pathogenesis and characterise FFA as a genetically predisposed immuno-inflammatory disorder driven by HLA-B*07:02.

HLA-C*06:02 genotype is a predictive biomarker of biologic treatment response in psoriasis.

BACKGROUND: Biologic therapies can be highly effective for the treatment of severe psoriasis, but response for individual patients can vary according to drug. Predictive biomarkers to guide treatment selection could improve patient outcomes and treatment cost-effectiveness. OBJECTIVE: We sought to test whether HLA-C*06:02, the primary genetic susceptibility allele for psoriasis, predisposes patients to respond differently to the 2 most commonly prescribed biologics for psoriasis: adalimumab (anti-TNF-α) and ustekinumab (anti-IL-12/23). METHODS: This study uses a national psoriasis registry that includes longitudinal treatment and response observations and detailed clinical data. HLA alleles were imputed from genome-wide genotype data for 1326 patients for whom 90% reduction in Psoriasis Area and Severity Index score (PASI90) response status was observed after 3, 6, or 12 months of treatment. We developed regression models of PASI90 response, examining the interaction between HLA-C*06:02 and drug type (adalimumab or ustekinumab) while accounting for potentially confounding clinical variables. RESULTS: HLA-C*06:02-negative patients were significantly more likely to respond to adalimumab than ustekinumab at all time points (most strongly at 6 months: odds ratio [OR], 2.95; P = 5.85 × 10-7), and the difference was greater in HLA-C*06:02-negative patients with psoriatic arthritis (OR, 5.98; P = 6.89 × 10-5). Biologic-naive patients who were HLA-C*06:02 positive and psoriatic arthritis negative demonstrated significantly poorer response to adalimumab at 12 months (OR, 0.31; P = 3.42 × 10-4). Results from HLA-wide analyses were consistent with HLA-C*06:02 itself being the primary effect allele. We found no evidence for genetic interaction between HLA-C*06:02 and ERAP1. CONCLUSION: This large observational study suggests that reference to HLA-C*06:02 status could offer substantial clinical benefit when selecting treatments for severe psoriasis.

Genome-wide meta-analysis implicates mediators of hair follicle development and morphogenesis in risk for severe acne.

Acne vulgaris is a highly heritable common, chronic inflammatory disease of the skin for which five genetic risk loci have so far been identified. Here, we perform a genome-wide association study of 3823 cases and 16,144 controls followed by meta-analysis with summary statistics from a previous study, with a total sample size of 26,722. We identify 20 independent association signals at 15 risk loci, 12 of which have not been previously implicated in the disease. Likely causal variants disrupt the coding region of WNT10A and a P63 transcription factor binding site in SEMA4B. Risk alleles at the 1q25 locus are associated with increased expression of LAMC2, in which biallelic loss-of-function mutations cause the blistering skin disease epidermolysis bullosa. These findings indicate that variation affecting the structure and maintenance of the skin, in particular the pilosebaceous unit, is a critical aspect of the genetic predisposition to severe acne.

Polygenic risk score analyses of symptoms and treatment response in an antipsychotic-naive first episode of psychosis cohort.

In this study, we aimed to test if the schizophrenia (SCZ) polygenic risk score (PRS) was associated with clinical symptoms in (a) the first episode of psychosis pre-treatment (FEP), (b) at nine weeks after initiation of risperidone treatment (FEP-9W) and (c) with the response to risperidone. We performed a detailed clinical assessment of 60 FEP patients who were antipsychotic-naive and, again, after nine weeks of standardized treatment with risperidone. After blood collection and DNA isolation, the samples were genotyped using the Illumina PsychArrayChip and then imputed. To calculate PRS, we used the latest available GWAS summary statistics from the Psychiatric Genomics Consortium wave-2 SCZ group as a training set. We used Poisson regression to test association between PRS and clinical measurements correcting for the four principal components (genotyping). We considered a p-value < 0.0014 (Bonferroni correction) as significant. First, we verified that the schizophrenia PRS was also able to distinguish cases from controls in this south-eastern Brazilian sample, with a similar variance explained to that seen in Northern European populations. In addition, within-cases analyses, we found that PRS is significantly correlated with baseline (pre-treatment) symptoms, as measured by lower clinical global assessment of functioning (-GAF), higher depressive symptoms and higher scores on a derived excitement factor. After standardized treatment for nine weeks, the correlation with GAF and the excitement factor disappeared while depressive symptoms became negatively associated with PRS. We conclude that drug (and other treatments) may confound attempts to understand the aetiological influence on symptomatology of polygenic risk scores. These results highlight the importance of studying schizophrenia, and other disorders, pre-treatment to understand the relationship between polygenic risk and phenotypic features.

Development of multivariable models to predict change in Body Mass Index within a clinical trial population of psychotic individuals.

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort.

Exome-wide association study reveals novel psoriasis susceptibility locus at TNFSF15 and rare protective alleles in genes contributing to type I IFN signalling.

Psoriasis is a common inflammatory skin disorder for which multiple genetic susceptibility loci have been identified, but few resolved to specific functional variants. In this study, we sought to identify common and rare psoriasis-associated gene-centric variation. Using exome arrays we genotyped four independent cohorts, totalling 11 861 psoriasis cases and 28 610 controls, aggregating the dataset through statistical meta-analysis. Single variant analysis detected a previously unreported risk locus at TNFSF15 (rs6478108; P = 1.50 × 10-8, OR = 1.10), and association of common protein-altering variants at 11 loci previously implicated in psoriasis susceptibility. We validate previous reports of protective low-frequency protein-altering variants within IFIH1 (encoding an innate antiviral receptor) and TYK2 (encoding a Janus kinase), in each case establishing a further series of protective rare variants (minor allele frequency < 0.01) via gene-wide aggregation testing (IFIH1: pburden = 2.53 × 10-7, OR = 0.707; TYK2: pburden = 6.17 × 10-4, OR = 0.744). Both genes play significant roles in type I interferon (IFN) production and signalling. Several of the protective rare and low-frequency variants in IFIH1 and TYK2 disrupt conserved protein domains, highlighting potential mechanisms through which their effect may be exerted.

The genome-wide expression effects of escitalopram and its relationship to neurogenesis, hippocampal volume, and antidepressant response.

Antidepressant-induced hippocampal neurogenesis (AHN) is hypothesized to contribute to increases in hippocampal volume among major depressive disorder patients after long-term treatment. Furthermore, rodent studies suggest AHN may be the cellular mechanism mediating the therapeutic benefits of antidepressants. Here, we perform the first investigation of genome-wide expression changes associated with AHN in human cells. We identify gene expression networks significantly activated during AHN, and we perform gene set analyses to probe the molecular relationship between AHN, hippocampal volume, and antidepressant response. The latter were achieved using genome-wide association summary data collected from 30,717 individuals as part of the ENIGMA Consortium (genetic predictors of hippocampal volume dataset), and data collected from 1,222 major depressed patients as part of the NEWMEDS Project (genetic predictors of response to antidepressants dataset). Our results showed that the selective serotonin reuptake inhibitor, escitalopram evoked AHN in human cells; dose-dependently increasing the differentiation of cells into neuroblasts, as well as increasing gliogenesis. Activated genome-wide expression networks relate to axon and microtubule formation, and ribosomal biogenesis. Gene set analysis revealed that gene expression changes associated with AHN were nominally enriched for genes predictive of hippocampal volume, but not for genes predictive of therapeutic response.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

OBJECTIVES: Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. METHODS: Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. RESULTS: Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. CONCLUSIONS: We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.