Biological Pleiotropy Research Articles

Genomic Correlation, Shared Loci, and Causal Relationship Between Bullous Pemphigoid and Atopic Dermatitis: A Large-Scale Genome-Wide Cross-Trait Analysis.

Bullous pemphigoid (BP) and atopic dermatitis (AD) are currently thought to be tightly related, yet studies of the mechanisms of co-morbidities are lacking. We obtained GWAS data for BP (N = 376,274) and AD (N = 796,661) from the Finnish Genetic Research Program dataset and the UK Biobank, separately. Then, the following four analyses were performed: (1) cross-trait linkage disequilibrium score regression (LDSC) to assess the genetic correlation between BP and AD, (2) cross-phenotype association analysis (CPASSOC) to identify multiple effector loci shared by BP and AD, (3) transcriptome-wide association study (TWAS) to determine whether their cross-organizational expression patterns share genes with a common biological mechanism of relevance, and (4) bidirectional Mendelian randomization (MR) analysis to assess bidirectional causal effects of BP and AD. We found a positive genetic association between BP and AD (rg = 0.5476, p = 0.0495) as well as identified four pleiotropic loci and 59 common genes affecting BP and AD. Bidirectional MR analysis suggested that BP promotes the risk of AD. We revealed a genetic link between BP and AD, which is associated with biological pleiotropy and causality. Awareness of the association between BP and AD helps dermatologists manage patients with these illnesses.

Genomic correlation, shared loci, and causal relationship between insomnia and psoriasis: a large-scale genome-wide cross-trait analysis.

Psoriasis and insomnia have co-morbidities, however, their common genetic basis is still unclear. We analyzed psoriasis and insomnia with summary statistics from genome-wide association studies. We first quantified overall genetic correlations, then ascertained multiple effector loci and expression-trait associations, and lastly, we analyzed the causal effects between psoriasis and insomnia. A prevalent genetic link between psoriasis and insomnia was found, four pleiotropic loci affecting psoriasis and insomnia were identified, and 154 genes were shared, indicating a genetic link between psoriasis and insomnia. Yet, there is no causal relationship between psoriasis and insomnia by two-sample Mendelian randomization. We discovered a genetic connection between insomnia and psoriasis driven by biological pleiotropy and unrelated to causation. Cross-trait analysis indicates a common genetic basis for psoriasis and insomnia. The results of this study highlight the importance of sleep management in the pathogenesis of psoriasis.

Shared genetic basis connects smoking behaviors and bone health: insights from a genome-wide cross-trait analysis.

Although the negative association of tobacco smoking with osteoporosis is well-documented, little is known regarding the shared genetic basis underlying these conditions. In this study, we aim to investigate a shared genetic architecture between smoking and heel estimated bone mineral density (eBMD), a reliable proxy for osteoporosis. We conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci and causal relationship of smoking with eBMD, leveraging summary statistics of the hitherto largest genome-wide association studies conducted in European ancestry for smoking initiation (Nsmoker = 1 175 108, Nnonsmoker = 1 493 921), heaviness (cigarettes per day, N = 618 489), cessation (Ncurrent smoker = 304 244, Nformer smoker = 843 028), and eBMD (N = 426 824). A significant negative global genetic correlation was found for smoking cessation and eBMD (${r}_g$ = -0.051, P = 0.01), while we failed to identify a significant global genetic correlation of smoking initiation or heaviness with eBMD. Partitioning the whole genome into independent blocks, we observed 6 significant shared local signals for smoking and eBMD, with 22q13.1 showing the strongest regional genetic correlation. Such a genetic overlap was further supported by 71 pleiotropic loci identified in the cross-trait meta-analysis. Mendelian randomization identified no causal effect of smoking initiation (beta = -0.003g/cm2, 95% CI = -0.033 to 0.027) or heaviness (beta = -0.017g/cm2, 95% CI = -0.072 to 0.038) on eBMD, but a putative causal effect of genetic predisposition to being a current smoker was associated with a lower eBMD compared to former smokers (beta = -0.100g/cm2, 95% CI = -0.181 to -0.018). Our study demonstrates a pronounced biological pleiotropy as well as a putative causal link between current smoking status and eBMD, providing novel insights into the primary prevention and modifiable intervention of osteoporosis by advocating individuals to avoid, reduce or quit smoking as early as possible.

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis

PurposeTo investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.MethodsOur study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.ResultsWith this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10−13), HbA1c (rg = 0.182, p = 4.14 × 10−6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10−6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER.ConclusionOur research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

Understanding the relationship between circulating lipids and risk of chronic kidney disease: a prospective cohort study and large-scale genetic analyses

BackgroundThis study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR).MethodsWe first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460).ResultsThere were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60–0.95; TG: HR = 1.08, 95%CI = 1.02–1.13) and global genetic correlations (HDL-C: {r}_{g} = − 0.132, P = 1.00 × 10–4; TG: {r}_{g} = 0.176; P = 2.66 × 10–5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85–0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed.ConclusionsOur work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD.Graphical

The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation

BackgroundThe correlation between human gut microbiota and psychiatric diseases has long been recognized. Based on the heritability of the microbiome, genome-wide association studies on human genome and gut microbiome (mbGWAS) have revealed important host-microbiome interactions. However, establishing causal relationships between specific gut microbiome features and psychological conditions remains challenging due to insufficient sample sizes of previous studies of mbGWAS. MethodsCross-cohort meta-analysis (via METAL) and multi-trait analysis (via MTAG) were used to enhance the statistical power of mbGWAS for identifying genetic variants and genes. Using two large mbGWAS studies (7,738 and 5,959 participants respectively) and12 disease-specific studies from the Psychiatric Genomics Consortium (PGC), we performed bidirectional two-sample mendelian randomization (MR) analyses between microbial features and psychiatric diseases (up to 500,199 individuals). Additionally, we conducted downstream gene- and gene-set-based analyses to investigate the shared biology linking gut microbiota and psychiatric diseases. ResultsMETAL and MTAG conducted in mbGWAS could boost power for gene prioritization and MR analysis. Increases in the number of lead SNPs and mapped genes were witnessed in 13/15 species and 5/10 genera after using METAL, and MTAG analysis gained an increase in sample size equivalent to expanding the original samples from 7% to 63%. Following METAL use, we identified a positive association between Bacteroides faecis and ADHD (OR, 1.09; 95 %CI, 1.02–1.16; P = 0.008). Bacteroides eggerthii and Bacteroides thetaiotaomicron were observed to be positively associated with PTSD (OR, 1.11; 95 %CI, 1.03–1.20; P = 0.007; OR, 1.11; 95 %CI, 1.01–1.23; P = 0.03). These findings remained stable across statistical models and sensitivity analyses. No genetic liabilities to psychiatric diseases may alter the abundance of gut microorganisms.Using biological annotation, we identified that those genes contributing to microbiomes (e.g., GRIN2A and RBFOX1) are expressed and enriched in human brain tissues. ConclusionsOur statistical genetics strategy helps to enhance the power of mbGWAS, and our genetic findings offer new insights into biological pleiotropy and causal relationship between microbiota and psychiatric diseases.

Migraine, chronic kidney disease and kidney function: observational and genetic analyses

Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank (N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine (Ncase/Ncontrol = 48,975/540,381), CKD (Ncase/Ncontrol = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85–1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression–trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98–1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01–0.04; P = 1.92 × 10−3), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.

Elucidating the patterns of pleiotropy and its biological relevance in maize.

Pleiotropy-when a single gene controls two or more seemingly unrelated traits-has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of biological pleiotropy across all maize phenotypes is largely unknown. Here, we investigate the extent to which biological pleiotropy impacts phenotypes within maize using GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assess the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide and large effect variants, leaving the prevalence of detectable pleiotropy relatively low.

A sex- and site-specific relationship between body mass index and osteoarthritis: evidence from observational and genetic analyses

We primarily aimed to investigate whether there are phenotypic and genetic links underlying body mass index (BMI) and overall osteoarthritis (OA). We then intended to explore whether the relationships differ across sexes and sites. We first evaluated the phenotypic association between BMI and overall OA using data from the UK Biobank. We then investigated the genetic relationship leveraging summary statistics of the hitherto largest genome-wide association studies performed for BMI and overall OA. Finally, we repeated all analyses in a sex- (female, male) and site- (knee, hip, spine) specific manner. Observational analysis suggested an increased hazard of diagnosed OA per 5kg/m2 increment in BMI (hazard ratio=1.38, 95% confidence interval (CI)=1.37-1.39). A positive overall genetic correlation was observed for BMI and OA (rg=0.43, P=4.72×10-133), corroborated by 11 significant local signals. Cross-trait meta-analysis identified 34 pleiotropic loci shared between BMI and OA, of which seven were novel. Transcriptome-wide association study revealed 29 shared gene-tissue pairs, targeting nervous, digestive, and exo/endocrine systems. Mendelian randomization demonstrated a robust BMI-OA causal relationship (odds ratio=1.47, 95% CI=1.42-1.52). A similar pattern of effects was observed in sex- and site-specific analyses, with BMI affecting OA comparably in both sexes and most strongly in the knee. Our work demonstrates an intrinsic relationship underlying BMI and overall OA, reflected by a pronounced phenotypic association, significant biological pleiotropy, and a putative causal link. Stratified analysis further reveals that the effects are distinct across sites and comparable across sexes.

Early socioeconomic adversity and young adult diabetic risk: an investigation of genetically informed biopsychosocial processes over the life course

ABSTRACT The present study investigated a comprehensive model that integrates contributions of early socioeconomic adversity (ESA) and multiple polygenic scores (PGSs) through different mechanisms leading to diabetic risk in early adulthood. The study used prospective, longitudinal data from the National Longitudinal Study of Adolescent and Adult Health (Add Health) with a sample of 5,728 youth of European ancestry. The results showed that both ESA and PGSs were involved in different mechanisms. ESA contributed additively to educational failures, BMI, depressive symptoms, and diabetes risk over the life course (an additive process). Also, ESA launched a cascading process that connected these outcomes in a successively contingent manner. In addition to ESA, youths’ multiple PGSs directly contributed to educational, psychological, and BMI outcomes. Multiple PGSs for education, BMI, and type 2 diabetes influenced not only youth outcomes that they were supposed to predict directly but also additional youth outcomes showing biological pleiotropy. The findings highlight the value of incorporating molecular genetic information into longitudinal developmental life course research and provide insight into malleable characteristics and appropriate timing for interventions addressing youth developmental and health outcomes.

A genome-wide cross-trait analysis identifies shared loci and causal relationships of type 2 diabetes and glycaemic traits with polycystic ovary syndrome

Aims/hypothesisThe link underlying abnormal glucose metabolism, type 2 diabetes and polycystic ovary syndrome (PCOS) that is independent of BMI remains unclear in observational studies. We aimed to clarify this association using a genome-wide cross-trait approach.MethodsSummary statistics from the hitherto largest genome-wide association studies conducted for type 2 diabetes, type 2 diabetes mellitus adjusted for BMI (T2DMadjBMI), fasting glucose, fasting insulin, 2h glucose after an oral glucose challenge (all adjusted for BMI), HbA1c and PCOS, all in populations of European ancestry, were used. We quantified overall and local genetic correlations, identified pleiotropic loci and expression–trait associations, and made causal inferences across traits.ResultsA positive overall genetic correlation between type 2 diabetes and PCOS was observed, largely influenced by BMI (rg=0.31, p=1.63×10–8) but also independent of BMI (T2DMadjBMI–PCOS: rg=0.12, p=0.03). Sixteen pleiotropic loci affecting type 2 diabetes, glycaemic traits and PCOS were identified, suggesting mechanisms of association that are independent of BMI. Two shared expression–trait associations were found for type 2 diabetes/T2DMadjBMI and PCOS targeting tissues of the cardiovascular, exocrine/endocrine and digestive systems. A putative causal effect of fasting insulin adjusted for BMI and type 2 diabetes on PCOS was demonstrated.Conclusions/interpretationWe found a genetic link underlying type 2 diabetes, glycaemic traits and PCOS, driven by both biological pleiotropy and causal mediation, some of which is independent of BMI. Our findings highlight the importance of controlling fasting insulin levels to mitigate the risk of PCOS, as well as screening for and long-term monitoring of type 2 diabetes in all women with PCOS, irrespective of BMI.Graphical abstract

A simple and rapid method for extraction and measurement of circulating sphingolipids using LC-MS/MS: a targeted lipidomic analysis.

Sphingolipids are a class of lipids with high structural diversity and biological pleiotropy. Mounting evidence supports a role for sphingolipids in regulating pathophysiology of cardiometabolic diseases, and they have been proposed as potential cardiometabolic biomarkers. Current methods for quantifying sphingolipids require laborious pretreatment and relatively large sample volumes, and cover limited species, hindering their application in epidemiological studies. Herein, we applied a time-, labor-, and sample-saving protocol simply using methanol for plasma sphingolipid extraction. It was compared with classical liquid-liquid extraction methods and showed significant advantages in terms of simplicity, sphingolipid coverage, and sample volume. By coupling the protocol with liquid chromatography using a wide-span mobile phase polarity parameter and tandem mass spectrometry operated in dynamic multiple reaction monitoring mode, 37 sphingolipids from 8 classes (sphingoid base, sphingoid base phosphate, ceramide-1-phosphate, lactosylceramide, hexosylceramide, sphingomyelin, ceramide, and dihydroceramide) were quantified within 16min, using only 10 μL of human plasma. The current method showed good performance in terms of linearity (R2 > 0.99), intra- and interbatch accuracy (70-123%) and precision (RSD < 12%), matrix effect (91-121%), recovery (96-101%), analyte chemical stability (deviation < 19%), and carryover (< 16%). We successfully applied this method to quantify 33 detectable sphingolipids from 579 plasma samples of an epidemiological study within 10days. The quantified sphingolipid concentrations were comparable with previous studies. Positive associations of ceramide C22:0/C24:0 and their precursors with homeostasis model assessment of insulin resistance suggested that the synthesis of the ceramides might be involved in insulin resistance. This novel method constitutes a simple and rapid approach to quantify circulating sphingolipids for epidemiological studies using targeted lipidomic analysis, which will help elucidate the sphingolipid-regulated pathways underlying cardiometabolic diseases.

Psychiatric risk gene transcription factor 4 preferentially regulates cortical interneuron neurogenesis during early brain development.

Genetic variants within or near the transcription factor 4 gene (TCF4) are robustly implicated in psychiatric disorders including schizophrenia. However, the biological pleiotropy poses considerable obstacles to dissect the potential relationship between TCF4 and those highly heterogeneous diseases. Through integrative transcriptomic analysis, we demonstrated that TCF4 is preferentially expressed in cortical interneurons during early brain development. Therefore, disruptions of interneuron development might be the underlying contribution of TCF4 perturbation to a range of neurodevelopmental disorders. Here, we performed chromatin immunoprecipitation sequencing (ChIP-seq) of TCF4 on human medial ganglionic eminence-like organoids (hMGEOs) to identify genome-wide TCF4 binding sites, followed by integration of multi-omics data from human fetal brain. We observed preferential expression of the isoform TCF4-B over TCF4-A. De novo motif analysis found that the identified 5916 TCF4 binding sites are significantly enriched for the E-box sequence. The predicted TCF4 targets in general have positively correlated expression levels with TCF4 in the cortical interneurons, and are primarily involved in biological processes related to neurogenesis. Interestingly, we found that TCF4 interacts with non-bHLH proteins such as FOS/JUN, which may underlie the functional specificity of TCF4 in hMGEOs. This study highlights the regulatory role of TCF4 in interneuron development and provides compelling evidence to support the biological rationale linking TCF4 to the developing cortical interneuron and psychiatric disorders.

Discordant associations of educational attainment with ASD and ADHD implicate a polygenic form of pleiotropy

Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are complex co-occurring neurodevelopmental conditions. Their genetic architectures reveal striking similarities but also differences, including strong, discordant polygenic associations with educational attainment (EA). To study genetic mechanisms that present as ASD-related positive and ADHD-related negative genetic correlations with EA, we carry out multivariable regression analyses using genome-wide summary statistics (N = 10,610–766,345). Our results show that EA-related genetic variation is shared across ASD and ADHD architectures, involving identical marker alleles. However, the polygenic association profile with EA, across shared marker alleles, is discordant for ASD versus ADHD risk, indicating independent effects. At the single-variant level, our results suggest either biological pleiotropy or co-localisation of different risk variants, implicating MIR19A/19B microRNA mechanisms. At the polygenic level, they point to a polygenic form of pleiotropy that contributes to the detectable genome-wide correlation between ASD and ADHD and is consistent with effect cancellation across EA-related regions.

Association and genetic overlap between clinical chemistry tests and migraine.

In this paper, we studied several serum clinical chemistry tests of cardiovascular disease (CVD), iron deficiency anemia, liver and kidney disorders in migraine. We first explored the association of 22 clinical chemistry tests with migraine risk in 697 migraine patients and 2722 controls. To validate and interpret association findings, cross-trait genetic analyses were conducted utilising genome-wide association study (GWAS) data comprising 23,986 to 452,264 individuals. Significant associations with migraine risk were identified for biomarkers of CVD risk, iron deficiency and liver dysfunction (odds ratios = 0.86-1.21; 1 × 10-4 < p < 3 × 10-2). Results from cross-trait genetic analyses corroborate the significant biomarker associations and indicate their relationship with migraine is more consistent with biological pleiotropy than causality. For example, association and genetic overlap between a lower level of HDL-C and increased migraine risk are due to shared biology rather than a causal relationship. Furthermore, additional genetic analyses revealed shared genetics among migraine, the clinical chemistry tests, and heart problems and iron deficiency anemia, but not liver disease. These findings highlight common biological mechanisms underlying migraine, heart problems and iron deficiency anemia and provide support for their investigation in the development of novel therapeutic and dietary interventions.

Assessing pleiotropy and mediation in genetic loci associated with chronic obstructive pulmonary disease.

Genetic association studies have increasingly recognized variant effects on multiple phenotypes. Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with environmental and genetic causes. Multiple genetic variants have been associated with COPD, many of which show significant associations to additional phenotypes. However, it is unknown if these associations represent biological pleiotropy or if they exist through correlation of related phenotypes ("mediated pleiotropy"). Using 6,670 subjects from the COPDGene study, we describe the association of known COPD susceptibility loci with other COPD-related phenotypes and distinguish if these act directly on the phenotypes (i.e., biological pleiotropy) or if the association is due to correlation (i.e., mediated pleiotropy). We identified additional associated phenotypes for 13 of 25 known COPD loci. Tests for pleiotropy between genotype and associated outcomes were significant for all loci. In cases of significant pleiotropy, we performed mediation analysis to test if SNPs had a direct association to phenotype. Most loci showed a mediated effect through the hypothesized causal pathway. However, many loci also had direct associations, suggesting causal explanations (i.e., emphysema leading to reduced lung function) are incomplete. Our results highlight the high degree of pleiotropy in complex disease-associated loci and provide novel insights into the mechanisms underlying COPD.

Genome-Wide Variants Shared Between Smoking Quantity and Schizophrenia on 15q25 Are Associated With CHRNA5 Expression in the Brain.

Cigarette smokers with schizophrenia consume more cigarettes than smokers in the general population. Schizophrenia and smoking quantity may have shared genetic liability. Genome-wide association studies (GWASs) of schizophrenia and smoking quantity have highlighted a biological pleiotropy in which a robust 15q25 locus affects both traits. To identify the genetic variants shared between these traits on 15q25, we used summary statistics from large-scale GWAS meta-analyses of schizophrenia in the Psychiatric Genomics Consortium 2 and smoking quantity assessed by cigarettes smoked per day in the Tobacco and Genetics Consortium. To evaluate the regulatory potential of the shared genetic variants, expression quantitative trait loci analysis in 10 postmortem brain regions was performed using the BRAINEAC dataset in 134 neuropathologically normal individuals. Twenty-two genetic variants on 15q25 were associated with both smoking quantity and schizophrenia at the genome-wide significance level (P < 5.00 × 10-8). Major alleles of all variants were associated with higher smoking quantity and risk of schizophrenia. These genetic variants were associated with PSMA4, CHRNA3, and CHRNB4 expression in specific brain regions (lowest P = 4.81 × 10-4) and with CHRNA5 expression in multiple brain regions (lowest P = 8.70 × 10-6). Risk-associated major alleles of these variants were commonly associated with higher expression in several brain regions, excluding the medulla, at the transcript level. In addition, the risk-associated major allele at rs637137 was associated with higher CHRNA5 expression at the specific exon level in multiple brain regions (lowest P = 2.37 × 10-5). Our findings suggest that genome-wide variants shared between smoking quantity and schizophrenia contribute to a common pathophysiology underlying these traits involving altered CHRNA5 expression in the brain.

9.1 GENOMICS AND PSYCHIATRIC DIAGNOSIS

BackgroundRecent genomic studies have begun to reveal the genetic architecture of psychiatric disorder and to give important insights into the relationship between the psychiatric syndromes that form the basis of current taxonomy. These studies have demonstrated the highly polygenic nature of psychiatric disorders, and have indicated that many individual genetic associations are shared across multiple disorders in a way that points to extensive biological pleiotropy and challenges the biological validity of existing diagnostic approaches.MethodsI will present genomic data, predominantly from the study of rare variants, that support the idea of a neurodevelopmental continuum, in which schizophrenia and bipolar disorder, together with childhood neurodevelopmental disorders, such as ID, ASD and ADHD represent the diverse range of outcomes that follow from disrupted or deviant brain development and furthermore that, within the neurodevelopmental continuum, severe mental illnesses occupy a gradient of decreasing neurodevelopmental impairment as follows: ID, ASD, schizophrenia and bipolar disorder. I will also present findings indicating that common genetic variation modifies the outcome of neurodevelopmental impairment explaining in part the diversity of psychiatric outcomes. Finally, I will explore how genetic data might be used to inform novel approaches to patient stratification which will be informative for prognosis and treatment response and facilitate the identification of novel drug targets.ResultsFinally, despite the undoubted complexity and the fact that much of the genetic risk remains unaccounted for at the DNA level, there are encouraging signs that the genes implicated in schizophrenia converge onto sets of plausible biological processes. In particular, the data point to synaptic function and histone modification and implicate mechanisms involved in brain plasticity that are important in development and in learning and cognition. While these are almost certainly not the only processes involved, they provide robust entry points for clinical and basic neuroscience research.DiscussionN/A

Associations of coffee genetic risk scores with consumption of coffee, tea and other beverages in the UK Biobank.

AimsTo evaluate the utility of coffee‐related genetic variants as proxies for coffee consumption in Mendelian randomization studies, by examining their association with non‐alcoholic beverage consumption (including subtypes of coffee and tea) and a range of socio‐demographic and life‐style factors.DesignObservational study of the association of genetic risk scores for coffee consumption with different types of non‐alcoholic beverage consumption.SettingUK general population.ParticipantsIndividuals of European ancestry aged 40–73 years from the UK Biobank between 2006 and 2010 (n = 114 316).MeasurementsGenetic risk scores were constructed using two, four and eight independent single nucleotide polymorphisms (SNPs) identified in genome‐wide association studies (GWAS) of coffee consumption. Drinks were self‐reported in a baseline questionnaire (all participants) and in detailed 24 dietary recall questionnaires in a subset (n = 48 692).FindingsGenetic risk scores explained up to 0.38, 0.19 and 0.76% of the variance in coffee, tea and combined coffee and tea consumption, respectively. Genetic risk scores demonstrated positive associations with both caffeinated and decaffeinated coffee and tea consumption, and with most subtypes of coffee consumption, but only with standard tea consumption. There was no clear evidence for positive associations with most other non‐alcoholic beverages, but higher genetic risk for coffee consumption was associated with lower daily water consumption. The genetic risk scores were associated with increased alcohol consumption, but not consistently with other socio‐demographic and life‐style factors.ConclusionsCoffee‐related genetic risk scores could be used as instruments for combined coffee and tea consumption in Mendelian randomization studies. However, associations observed with alcohol consumption require further investigation to determine whether these are due to causal effects of coffee and tea consumption or biological pleiotropy.

Molecular genetics of the transcription factor GLIS3 identifies its dual function in beta cells and neurons

The GLIS family zinc finger 3 isoform (GLIS3) is a risk gene for Type 1 and Type 2 diabetes, glaucoma and Alzheimer's disease endophenotype. We identified GLIS3 binding sites in insulin secreting cells (INS1) (FDR q<0.05; enrichment range 1.40–9.11 fold) sharing the motif wrGTTCCCArTAGs, which were enriched in genes involved in neuronal function and autophagy and in risk genes for metabolic and neuro-behavioural diseases. We confirmed experimentally Glis3-mediated regulation of the expression of genes involved in autophagy and neuron function in INS1 and neuronal PC12 cells. Naturally-occurring coding polymorphisms in Glis3 in the Goto-Kakizaki rat model of type 2 diabetes were associated with increased insulin production in vitro and in vivo, suggestive alteration of autophagy in PC12 and INS1 and abnormal neurogenesis in hippocampus neurons. Our results support biological pleiotropy of GLIS3 in pathologies affecting β-cells and neurons and underline the existence of trans‑nosology pathways in diabetes and its co-morbidities.