GWAS Findings Research Articles

Exome sequencing identifies genes for socioeconomic status in 350,770 individuals

Socioeconomic status (SES) is a critical factor in determining health outcomes and is influenced by genetic and environmental factors. However, our understanding of the genetic structure of SES remains incomplete. Here, we conducted a large-scale exome study of SES markers (household income, occupational status, educational attainment, and social deprivation) in 350,770 individuals. For rare coding variants, we identified 56 significant associations by gene-based collapsing tests, unveiling 7 additional SES-associated genes (NRN1, CCDC36, RHOB, EP400, NCAM1, TPTEP2-CSNK1E, and LINC02881). Exome-wide single common variant analysis revealed nine lead single-nucleotide polymorphisms (SNPs) associated with household income and 34 lead SNPs associated with EduYears, replicating previous GWAS findings. The gene-environment correlations had a substantial impact on the genetic associations with SES, as indicated by the significantly increased P values in several associations after controlling for geographic regions. Furthermore, we observed the pleiotropic effects of SES-associated genetic factors on a wide range of health outcomes, such as cognitive function, psychosocial status, and diabetes. This study highlights the contribution of coding variants to SES and their associations with health phenotypes.

TESC overexpression mitigates amyloid-β-induced hippocampal atrophy and memory decline

Background and objectivesGenome-wide association studies (GWASs) have identified numerous candidate genes for human brain-imaging phenotypes; however, the biological relevance of many of these genes remains unconfirmed. This study aimed to investigate the causal relationships among tescalcin (TESC) (a GWAS-indicated gene), hippocampal volume, Alzheimer’s disease (AD), and the underlying biological mechanisms. MethodsHuman transcriptional data were analyzed to confirm relative TESC expression in the hippocampus. In cell experiments, RNA-seq analysis was used to identify the potential biological pathways for TESC overexpression, and immunofluorescence imaging and cell viability assays were used to evaluate the effect of TESC overexpression on neuronal structure and survival. In animal experiments, the effects of TESC overexpression on hippocampal volume and cognitive function in normal mice and amyloid-β (Aβ)-induced AD mice were investigated by 9.4 T magnetic resonance imaging and behavioral tests. Underlying mechanisms were further assessed via western blotting and electrophysiological recordings. ResultsHuman transcriptional data demonstrated that TESC is primarily expressed in the hippocampus and neurons. TESC overexpression enhanced the viability of HT22 cells and reduced Aβ-induced cell death. In mouse models, Tesc-overexpressing mice revealed increased hippocampal volume, likely owing to enhanced cell viability and long-term potentiation (LTP), and reducing apoptotic- and oxidation-induced hippocampal damage. TESC overexpression could significantly mitigate Aβ-induced hippocampal atrophy and memory impairment, potentially by reducing Aβ-induced neuronal apoptosis and LTP weakening. ConclusionThis study exemplifies the translation of GWAS findings into actionable biological knowledge and suggests that upregulation of TESC may offer a promising therapeutic strategy for AD.

Genome-wide association study of copy number variations in Parkinson's disease.

Our study investigates the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data, aiming to uncover novel genetic mechanisms and improve the understanding of the role of CNVs in sporadic PD. We applied a sliding window approach to perform CNV-GWAS and conducted genome-wide burden analyses on CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium. We identified 14 genome-wide significant CNV loci associated with PD, including one deletion and 13 duplications. Among these, duplications in 7q22.1, 11q12.3 and 7q33 displayed the highest effect. Two significant duplications overlapped with PD-related genes SNCA and VPS13C, but none overlapped with recent significant SNP-based GWAS findings. Five duplications included genes associated with neurological disease, and four overlapping genes were dosage-sensitive and intolerant to loss-of-function variants. Enriched pathways included neurodegeneration, steroid hormone biosynthesis, and lipid metabolism. In early-onset cases, four loci were significantly associated with EOPD, including three known duplications and one novel deletion in PRKN. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. This is the largest CNV-based GWAS in PD identifying novel CNV regions and confirming the significant CNV burden in EOPD, primarily driven by the PRKN gene, warranting further investigation.

Unraveling metabolic stress response in dairy cows: Genetic control of plasma biomarkers throughout lactation and the transition period

Breeding animals able to effectively respond to stress could be a long-term, sustainable, and affordable strategy to improve resilience and welfare in livestock systems. In the present study, the concentrations of 29 plasma biomarkers were used as candidate endophenotypes for metabolic stress response in single-SNP, gene- and haplotype-based GWAS using 739 healthy lactating Italian Holstein cows and 88,271 variants. Significant genetic associations were found in all the 3 GWAS approaches for plasma γ-glutamyl transferase concentration on BTA17, for paraoxonase on BTA4, and for alkaline phosphatase and zinc on BTA2. On these chromosomes, single-SNP and gene-based chromosome-wide association studies were performed, confirming GWAS findings. The signals identified for paraoxonase, γ-glutamyl transferase, and alkaline phosphatase were in proximity to the genes coding for them. The heritability of these 4 biomarkers ranged from moderate to high (from 0.39 to 0.54). Plasma biomarkers are known to undergo large changes in concentration during metabolic stress in the transition period, with an interindividual variability in the rate of change and recovery time. Genetics may account in part for these differences. To assess this, we studied a subset of 139 periparturient cows homozygous at 3 SNPs known to be respectively associated with concentration of plasma ceruloplasmin, paraoxonase, and γ-glutamyl transferase. We compared the immune-metabolic profile measured in plasma at -7, +5, and +30 d relative to calving between groups of opposite homozygotes. A significant effect of the genotype was found on paraoxonase and γ-glutamyl transferase plasma concentration at all the 3 time points. No evidence for genotype effect was detected for ceruloplasmin. Understanding the genetic control underlying metabolic stress response may suggest new approaches to foster resilience in dairy cows.

Leveraging the transcriptome to further our understanding of GWAS findings: eQTLs associated with genes related to LDL and LDL subclasses, in a cohort of African Americans.

Background: GWAS discoveries often pose a significant challenge in terms of understanding their underlying mechanisms. Further research, such as an integration with expression quantitative trait locus (eQTL) analyses, are required to decipher the mechanisms connecting GWAS variants to phenotypes. An eQTL analysis was conducted on genes associated with low-density lipoprotein (LDL) cholesterol and its subclasses, with the aim of pinpointing genetic variants previously implicated in GWAS studies focused on lipid-related traits. Notably, the study cohort consisted of African Americans, a population characterized by a heightened prevalence of hypercholesterolemia. Methods: A comprehensive differential expression (DE) analysis was undertaken, with a dataset of 17,948 protein-coding mRNA transcripts extracted from the whole-blood transcriptomes of 416 samples to identify mRNA transcripts associated with LDL, with further granularity delineated between small LDL and large LDL subclasses. Subsequently, eQTL analysis was conducted with a subset of 242 samples for which whole-genome sequencing data were available to identify single-nucleotide polymorphisms (SNPs) associated with the LDL-related mRNA transcripts. Lastly, plausible functional connections were established between the identified eQTLs and genetic variants reported in the GWAS catalogue. Results: DE analysis revealed 1,048, 284, and 94 mRNA transcripts that exhibited differential expression in response to LDL, small LDL, and large LDL, respectively. The eQTL analysis identified a total of 9,950 significant SNP-mRNA associations involving 6,955 SNPs including a subset 101 SNPs previously documented in GWAS of LDL and LDL-related traits. Conclusion: Through comprehensive differential expression analysis, we identified numerous mRNA transcripts responsive to LDL, small LDL, and large LDL. Subsequent eQTL analysis revealed a rich landscape of eQTL-mRNA associations, including a subset of eQTL reported in GWAS studies of LDL and related traits. The study serves as a testament to the important role of integrative genomics in unraveling the enigmatic GWAS relationships between genetic variants and the complex fabric of human traits and diseases.

How to translate genetic findings into clinical applications in spondyloarthritis?

Spondyloarthritis (SpA) is characterized by a strong genetic predisposition evidenced by the identification of up to 50 susceptibility loci, in addition to HLA-B27, the major genetic factor associated with the disease. These loci have not only deepened our understanding of disease pathogenesis but also offer the potential to improve disease management. Diagnostic delay is a major issue in SpA. HLA-B27 testing is widely used as diagnostic biomarker in SpA but its predictive value is limited. Several attempts have been made to develop more sophisticated polygenic risk score (PRS). However, these scores currently offer very little improvement as compared to HLA-B27 and are still difficult to implement in clinical routine. Genetics might also help to predict disease outcome including treatment response. Several genetic variants have been reported to be associated with radiographic damage or with poor response to TNF blockers, unfortunately with lack of coherence across studies. Large-scale studies should be conducted to obtain more robust findings. Genetic and genomic evidence in complex diseases can be further used to support the identification of new drug targets and to repurpose existing drugs. Although not fully driven by genetics, development of IL-17 blockers has been facilitated by the discovery of the association between IL23R variants and SpA. Development of recent approaches combining GWAS findings with functional genomics will help to prioritize new drug targets in the future. Although very promising, translational genetics in SpA remains challenging and will require a multidisciplinary approach that integrates genetics, genomics, immunology, and clinical research.

Deep trans‐omic network fusion for altered functional interactions underlying Alzheimer’s Disease

AbstractBackgroundMulti‐omic data like genotype, gene expression and protein expression have been increasingly explored in post‐GWAS era to interpret GWAS findings and to gain more insight of the Alzheimer’s disease (AD) mechanism. However, each ‐omics data type is usually examined individually and identified genetic variations, genes and proteins are not necessarily functionally related.MethodWe used GWAS genotype, RNA‐Seq gene expression, and protein expression data from 133 subjects of ROS/MAP Project for original study and 121 subjects of Mount Sinai Brain Bank (MSBB) for replication (Fig. 1a). The multi‐omic data pre‐processing steps were shown in Fig. 1b. We proposed a new interpretable deep neural network MoFNet, extended from Varmole [1], to jointly model the prior knowledge of functional interactions using ROS/MAP cohort (Fig. 1c). It aimed to identify a subnetwork of functional interactions from prior knowledge that are both predictive of AD and evidenced by multi‐omic data. Particularly, prior functional interaction network was embedded into the architecture of MoFNet in a way that it resembles the information flow from DNA to gene and protein.ResultThe proposed model MoFNet significantly outperformed all other state‐of‐art classifiers when evaluated using multi‐omic data from ROS/MAP cohort (Table 1). It yielded three major multi‐omic sub‐networks related to innate immune system, clearance of mis‐folded proteins, and neurotransmitter release respectively (Fig. 2a). One subnetwork includes all the major members of the SNARE complex, an essential mediator of synaptic vesicle fusion. Majority of our identified genes/proteins are related to synaptic activities in neuronal, astrocyte and microglial cells. Differential expression analysis show MoFNet returned more genes and proteins due to functional connections (Fig. 2b). Around 50% of these findings were replicated in another independent cohort (MSBB).ConclusionOur identified gene/proteins are highly related to synaptic vesicle function. Altered regulation or expression of these genes/proteins could cause disruption in neuron‐neuron or neuron‐glia cross talk and further lead to neuronal and synapse loss in AD. Further investigation of these identified genes/proteins could possibly help decipher the mechanisms underlying synaptic dysfunction in AD, and ultimately inform therapeutic strategies to modify AD progression in the early stage. [1] Nguyen et al., Bioinformatics, 2021.

Sex differences in the polygenic architecture of hearing problems in adults

BackgroundHearing problems (HP) in adults are common and are associated with several comorbid conditions. Its prevalence increases with age, reflecting the cumulative effect of environmental factors and genetic predisposition. Although several risk loci have been already identified, HP biology and epidemiology are still insufficiently investigated by large-scale genetic studies.MethodsLeveraging the UK Biobank, the Nurses’ Health Studies (I and II), the Health Professionals Follow-up Study, and the Million Veteran Program, we conducted a comprehensive genome-wide investigation of HP in 748,668 adult participants (discovery N = 501,825; replication N = 226,043; cross-ancestry replication N = 20,800). We leveraged the GWAS findings to characterize HP polygenic architecture, exploring sex differences, polygenic risk across ancestries, tissue-specific transcriptomic regulation, cause-effect relationships with genetically correlated traits, and gene interactions with HP environmental risk factors.ResultsWe identified 54 risk loci and demonstrated that HP polygenic risk is shared across ancestry groups. Our transcriptomic regulation analysis highlighted the potential role of the central nervous system in HP pathogenesis. The sex-stratified analyses showed several additional associations related to peripheral hormonally regulated tissues reflecting a potential role of estrogen in hearing function. This evidence was supported by the multivariate interaction analysis that showed how genes involved in brain development interact with sex, noise pollution, and tobacco smoking in relation to their HP associations. Additionally, the genetically informed causal inference analysis showed that HP is linked to many physical and mental health outcomes.ConclusionsThe results provide many novel insights into the biology and epidemiology of HP in adults. Our sex-specific analyses and transcriptomic associations highlighted molecular pathways that may be targeted for drug development or repurposing. Additionally, the potential causal relationships identified may support novel preventive screening programs to identify individuals at risk.

Genetic variation in cis-regulatory domains suggests cell type-specific regulatory mechanisms in immunity

Studying the interplay between genetic variation, epigenetic changes, and regulation of gene expression is crucial to understand the modification of cellular states in various conditions, including immune diseases. In this study, we characterize the cell-specificity in three key cells of the human immune system by building cis maps of regulatory regions with coordinated activity (CRDs) from ChIP-seq peaks and methylation data. We find that only 33% of CRD-gene associations are shared between cell types, revealing how similarly located regulatory regions provide cell-specific modulation of gene activity. We emphasize important biological mechanisms, as most of our associations are enriched in cell-specific transcription factor binding sites, blood-traits, and immune disease-associated loci. Notably, we show that CRD-QTLs aid in interpreting GWAS findings and help prioritize variants for testing functional hypotheses within human complex diseases. Additionally, we map trans CRD regulatory associations, and among 207 trans-eQTLs discovered, 46 overlap with the QTLGen Consortium meta-analysis in whole blood, showing that mapping functional regulatory units using population genomics allows discovering important mechanisms in the regulation of gene expression in immune cells. Finally, we constitute a comprehensive resource describing multi-omics changes to gain a greater understanding of cell-type specific regulatory mechanisms of immunity.

Why does the X chromosome lag behind autosomes in GWAS findings?

The X-chromosome is among the largest human chromosomes. It differs from autosomes by a number of important features including hemizygosity in males, an almost complete inactivation of one copy in females, and unique patterns of recombination. We used data from the Catalog of Published Genome Wide Association Studies to compare densities of the GWAS-detected SNPs on the X-chromosome and autosomes. The density of GWAS-detected SNPs on the X-chromosome is 6-fold lower compared to the density of the GWAS-detected SNPs on autosomes. Differences between the X-chromosome and autosomes cannot be explained by differences in the overall SNP density, lower X-chromosome coverage by genotyping platforms or low call rate of X-chromosomal SNPs. Similar differences in the density of GWAS-detected SNPs were found in female-only GWASs (e.g. ovarian cancer GWASs). We hypothesized that the lower density of GWAS-detected SNPs on the X-chromosome compared to autosomes is not a result of a methodological bias, e.g. differences in coverage or call rates, but has a real underlying biological reason-a lower density of functional SNPs on the X-chromosome versus autosomes. This hypothesis is supported by the observation that (i) the overall SNP density of X-chromosome is lower compared to the SNP density on autosomes and that (ii) the density of genic SNPs on the X-chromosome is lower compared to autosomes while densities of intergenic SNPs are similar.

Deciphering the Effect of Different Genetic Variants on Hippocampal Subfield Volumes in the General Population.

The aim of this study was to disentangle the effects of various genetic factors on hippocampal subfield volumes using three different approaches: a biologically driven candidate gene approach, a hypothesis-free GWAS approach, and a polygenic approach, where AD risk alleles are combined with a polygenic risk score (PRS). The impact of these genetic factors was investigated in a large dementia-free general population cohort from the Study of Health in Pomerania (SHIP, n = 1806). Analyses were performed using linear regression models adjusted for biological and environmental risk factors. Hippocampus subfield volume alterations were found for APOE ε4, BDNF Val, and 5-HTTLPR L allele carriers. In addition, we were able to replicate GWAS findings, especially for rs17178139 (MSRB3), rs1861979 (DPP4), rs7873551 (ASTN2), and rs572246240 (MAST4). Interaction analyses between the significant SNPs as well as the PRS for AD revealed no significant results. Our results confirm that hippocampal volume reductions are influenced by genetic variation, and that different variants reveal different association patterns that can be linked to biological processes in neurodegeneration. Thus, this study underlines the importance of specific genetic analyses in the quest for acquiring deeper insights into the biology of hippocampal volume loss, memory impairment, depression, and neurodegenerative diseases.

A Network‐based Deep Learning Framework Translates GWAS and Multi‐Omics Findings to Pathobiology and Drug Repurposing for Alzheimer’s Disease

AbstractBackgroundHuman genome sequencing studies have identified numerous loci associated with complex diseases, including Alzheimer’s disease (AD). However, translating human genetic and genomic findings (i.e., genome‐wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge. Today, artificial intelligence and deep learning approaches that identify new risk genes and drug targets from human genome sequencing findings are enabling a more complete mechanistic understanding of disease biology. This is facilitating more rapid development of targeted therapeutic interventions for AD.MethodWe presented a network topology‐based deep learning framework to identify disease‐associated genes (NETTAG). NETTAG integrates multi‐genomics data and the human protein‐protein interactome to infer putative risk genes and drug targets impacted by GWAS loci. Specifically, we leveraged non‐coding GWAS loci effects on expression quantitative trait loci (eQTLs), histone‐QTLs, transcription factor binding‐QTLs, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions. The fundamental premise of NETTAG is that disease risk genes exhibit distinct functional characteristics compared to non‐risk genes, and can therefore be distinguished by their aggregated genomic features under the human protein interactome.ResultApplying NETTAG to the latest AD GWAS data, we identified 156 putative AD‐risk genes (i.e., APOE, BIN1, GSK3B, MARK4, and PICALM). We showed that predicted risk genes are: 1) significantly enriched in AD‐related pathobiological pathways, 2) more likely to be differentially expressed in transcriptomes and proteomes of AD brains, and 3) enriched in druggable targets with approved medicines. Specifically, we showed that NETTAG‐predicted genes (e.g., MEF2D, CPLX2, KLF4, ACTL6B, P2RX7 and etc.) are differentially expressed in AD‐associated microglia and astrocytes from single‐nuclei RNA‐sequencing data of human postmortem brains with varying degrees of AD neurobiology. Via network‐based prediction, we identified multiple repurposable drug candidates (i.e., choline, deferoxamine and ibudilast) for potential treatment of AD.ConclusionOur findings suggest that understanding human pathobiology and therapeutic development could benefit from network‐based deep learning methodology that utilizes GWAS findings with multimodal genomic analyses.

Manganese efflux transporter SLC30A10 missense polymorphism T95I associated with liver injury retains manganese efflux activity.

The activity of the manganese (Mn) efflux transporter SLC30A10 in the liver and intestines is critical for Mn excretion and preventing Mn toxicity. Homozygous loss-of-function mutations in SLC30A10 are a well-established cause of hereditary Mn toxicity. But, the relationship between more common SLC30A10 polymorphisms, Mn homeostasis, and disease is only recently emerging. In 2021, the first coding SNP in SLC30A10 (T95I) was associated with liver disease raising the hypothesis that the T95I substitution may induce disease by inhibiting the Mn efflux function of SLC30A10. Here, we test this hypothesis using structural, viability, and metal quantification approaches. Analyses of a predicted structure of SLC30A10 revealed that the side chain of T95 pointed away from the putative Mn-binding cavity, raising doubts about the impact of the T95I substitution on SLC30A10 function. In HeLa or HepG2 cells, overexpression of SLC30A10-WT or T95I resulted in comparable reductions of intracellular Mn levels and protection against Mn-induced cell death. Furthermore, ΔSLC30A10 HepG2 cells, generated using CRISPR/Cas9, exhibited elevated Mn levels and heightened sensitivity to Mn-induced cell death, and these phenotypic changes were similarly rescued by expression of SLC30A10-WT or T95I. Finally, turnover rates of SLC30A10-WT or T95I were also comparable. In summary, our results indicate that the Mn transport activity of SLC30A10-T95I is essentially comparable to the WT protein. Our findings imply that SLC30A10-T95I either has a complex association with liver injury that extends beyond the simple reduction in SLC30A10 activity or alternatively the T95I mutation lacks a causal role in liver disease.NEW & NOTEWORTHY This study demonstrates that the T95I polymorphism in the manganese transporter SLC30A10, which has been associated with liver disease in human GWAS studies, does not impact transporter function in cell culture. These findings raise doubts about the causal relationship of the T95I polymorphism with human disease and highlight the importance of validating GWAS findings using mechanistic approaches.

Antihypertensive Medication Class and the Risk of Dementia and Cognitive Decline in Older Adults: A Secondary Analysis of the Prospective HELIAD Cohort

It is unclear whether the main antihypertensive medication classes (diuretics, calcium channel blockers, beta-blockers, angiotensin converting enzyme inhibitors, and angiotensin receptor blockers (ARBs)) are associated with different risks of cognitive decline. Published evidence is conflicting and stems mainly from observational studies. To investigate the differential effects of antihypertensives on the risks of developing dementia and cognitive decline, with a specific focus on the vascular component of the mechanisms underlying these interactions. Older adults with a history of hypertension and without dementia were drawn from the population-based HELIAD cohort. Age-, gender-, education-, and antihypertensive medication- (five dichotomous exposures) adjusted Cox proportional-hazards models and generalized estimating equations were performed to appraise the associations of baseline antihypertensive therapy with dementia incidence and cognitive decline (quantified using a comprehensive neuropsychological battery). Analyses were subsequently adjusted for clinical vascular risk (dyslipidemia, diabetes mellitus, smoking, cardiovascular, and cerebrovascular history) and genetic susceptibility to stroke (using polygenic risk scores generated according to the MEGASTROKE consortium GWAS findings). A total of 776 predominantly female participants (73.61±4.94 years) with hypertension and a mean follow-up of 3.02±0.82 years were analyzed. Baseline treatment was not associated with the risk of incident dementia. ARB users experienced a slower yearly global cognitive [2.5% of a SD, 95% CI = (0.1, 4.9)] and language [4.4% of a SD, 95% CI = (1.4, 7.4)] decline compared to non-users. The fully adjusted model reproduced similar associations for both global cognitive [β= 0.027, 95% CI = (-0.003, 0.057)], and language decline [β= 0.063, 95% CI = (0.023, 0.104)]. ARBs may be superior to other antihypertensive agents in the preservation of cognition, an association probably mediated by vascular-independent mechanisms.

GWAS of Chronic Spontaneous Urticaria Reveals Genetic Overlap with Autoimmune Diseases, Not Atopic Diseases

Although chronic spontaneous urticaria (CSU) is a common disease, GWASs of CSU are lacking. We aimed to identify susceptibility SNPs by performing a GWAS in Chinese Han adults with CSU. The discovery cohort included 430 CSU cases and 482 healthy controls. The GWAS findings were validated in 800 CSU cases and 900 healthy controls. Genetic, functional enrichment, and bioinformatic analyses of genome-wide significant SNPs were performed to assess the association between CSU and autoimmunity or atopy. Five genome-wide significant SNPs were identified: rs434124/LILRA3, rs61986182/IGHG1/2, rs73075571/TDGF1, rs9378141/HLA-G, and rs3789612/PTPN22. The first four SNPs were in linkage disequilibrium with autoimmune-related diseases‒associated SNPs and were cis-expression quantitative trait loci in immune cells. The five SNPs-annotated genes were significantly enriched in immune processes. Higher polygenic risk scores and allele frequencies of rs3789612∗T, rs9378141∗C, and rs73075571∗G were significantly associated with autoimmune-related CSU phenotypes, including positive antithyroglobulin IgG, positive anti-FcεRIα IgG, total IgE <40 IU/ml, and positive antithyroid peroxidase IgG but not with atopic or allergic sensitized CSU phenotypes. This GWAS of CSU identifies five risk loci and reveals that CSU shares genetic overlap with autoimmune diseases and that genetic factors predisposing to CSU mainly manifest through associations with autoimmune traits.

A functional neuroimaging association study on the interplay between two schizophrenia genome-wide associated genes (CACNA1C and ZNF804A).

The CACNA1C and the ZNF804A genes are among the most relevant schizophrenia GWAS findings. Recent evidence shows that the interaction of these genes with the schizophrenia diagnosis modulates brain functional response to averbal fluencytask. To better understand how these genes might influence the risk for schizophrenia, we aimed to study the interplay between CACNA1C and ZNF804A on working memorybrain functional correlates. The analyses included functional and behavioural N-back taskdata (obtained from an fMRI protocol) and CACNA1C-rs1006737 and ZNF804A-rs1344706 genotypes for 78 healthy subjects and 78 patients with schizophrenia (matched for age, sex and premorbid IQ). We tested the effects of the epistasis between these genes as well as of the three-way interaction (CACNA1C×ZNAF804A×diagnosis) on working memory-associated activity (N-back: 2-back vs 1-back). We detected a significant CACNA1C×ZNAF804A interaction on working memory functional response in regions comprising the ventral caudate medially and within the left hemisphere, the superior and inferior orbitofrontal gyrus, the superior temporal pole and the ventral-anterior insula. The individuals with the GWAS-identified risk genotypes (CACNA1C-AA/AG and ZNF804A-AA) displayed a reduced working memory modulation response. This genotypic combination was also associated with opposite brain activity patterns between patients and controls. While further research will help to comprehend the neurobiological mechanisms of this interaction, our data highlight the role of the epistasis between CACNA1C and ZNF804A in the functional mechanisms underlying the pathophysiology of schizophrenia.

Back-translating GWAS findings to animal models reveals a role for Hgfac and Slc39a8 in alcohol and nicotine consumption

Alcohol and tobacco are the most commonly used addictive substances, with high comorbidity rates between alcohol use disorder and tobacco use disorder. Risk for alcohol and nicotine addiction is highly heritable, and they share common genetic factors. A GWAS in over 1 million individuals has revealed 566 genetic variants in 406 loci associated with multiple stages of alcohol and tobacco use. Three novel genes—SLC39A8, GRK4 and HGFAC—within loci associated with altered alcoholic drinks per week (ADW) or cigarettes per day (CPD) were selected to further study their role in alcohol and tobacco use disorder. The role of these genes was assessed using the two-bottle choice addiction paradigm in transgenic mice for each of the genes. We found significant decreases in chronic alcohol consumption and preference in female Hgfac knockout (KO) mice, and decreased nicotine preference in male Hgfac KO compared with wild-type (WT) mice. Additionally, male Slc39a8 hypomorph mice showed greater overall nicotine preference compared with WT mice, while no differences were detected for Grk4 KO mice in alcohol or nicotine consumption and preference in either sex. Thus, this study implicates Hgfac and Slc39a8 in alcohol and tobacco use in a sex-specific manner.

Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains

BackgroundLarge-scale genome-wide association studies have successfully identified many genetic variants significantly associated with Alzheimer’s disease (AD), such as rs429358, rs11038106, rs723804, rs13591776, and more. The next key step is to understand the function of these SNPs and the downstream biology through which they exert the effect on the development of AD. However, this remains a challenging task due to the tissue-specific nature of transcriptomic and proteomic data and the limited availability of brain tissue.In this paper, instead of using coupled transcriptomic data, we performed an integrative analysis of existing GWAS findings and expression quantitative trait loci (eQTL) results from AD-related brain regions to estimate the transcriptomic alterations in AD brain.ResultsWe used summary-based mendelian randomization method along with heterogeneity in dependent instruments method and were able to identify 32 genes with potential altered levels in temporal cortex region. Among these, 10 of them were further validated using real gene expression data collected from temporal cortex region, and 19 SNPs from NECTIN and TOMM40 genes were found associated with multiple temporal cortex imaging phenotype.ConclusionSignificant pathways from enriched gene networks included neutrophil degranulation, Cell surface interactions at the vascular wall, and Regulation of TP53 activity which are still relatively under explored in Alzheimer’s Disease while also encouraging a necessity to bind further trans-eQTL effects into this integrative analysis.

Dissecting the cross-trait effects of the FOXP2 GWAS hit on clinical and brain phenotypes in adults with ADHD.

The Forkhead box P2 (FOXP2) encodes for a transcription factor with a broad role in embryonic development. It is especially represented among GWAS hits for neurodevelopmental disorders and related traits, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, neuroticism, and risk-taking behaviors. While several functional studies are underway to understand the consequences of FOXP2 variation, this study aims to expand previous findings to clinically and genetically related phenotypes and neuroanatomical features among subjects with ADHD. The sample included 407 adults with ADHD and 463 controls. Genotyping was performed on the Infinium PsychArray-24 BeadChip, and the FOXP2 gene region was extracted. A gene-wide approach was adopted to evaluate the combined effects of FOXP2 variants (n = 311) on ADHD status, severity, comorbidities, and personality traits. Independent risk variants presenting potential functional effects were further tested for association with cortical surface areas in a subsample of cases (n = 87). The gene-wide analyses within the ADHD sample showed a significant association of the FOXP2 gene with harm avoidance (P = 0.001; PFDR = 0.015) and nominal associations with hyperactivity symptoms (P = 0.026; PFDR = 0.130) and antisocial personality disorder (P = 0.026; PFDR = 0.130). An insertion/deletion variant (rs79622555) located downstream of FOXP2 was associated with the three outcomes and nominally with the surface area of superior parietal and anterior cingulate cortices. Our results extend and refine previous GWAS findings pointing to a role of FOXP2 in several neurodevelopment-related phenotypes, mainly those involving underlying symptomatic domains of self-regulation and inhibitory control. Taken together, the available evidence may constitute promising insights into the puzzle of the FOXP2-related pathophysiology.

Local genetic variation of inflammatory bowel disease in Basque population and its effect in risk prediction

Inflammatory bowel disease (IBD) is characterised by chronic inflammation of the gastrointestinal tract. Although its aetiology remains unknown, environmental and genetic factors are involved in its development. Regarding genetics, more than 200 loci have been associated with IBD but the transferability of those signals to the Basque population living in Northern Spain, a population with distinctive genetic background, remains unknown. We have analysed 5,411,568 SNPs in 498 IBD cases and 935 controls from the Basque population. We found 33 suggestive loci (p < 5 × 10−6) in IBD and its subtypes, namely Crohn’s Disease (CD) and Ulcerative Colitis (UC), detecting a genome-wide significant locus located in HLA region in patients with UC. Those loci contain previously associated genes with IBD (IL23R, JAK2 or HLA genes) and new genes that could be involved in its development (AGT, BZW2 or FSTL1). The overall genetic correlation between European populations and Basque population was high in IBD and CD, while in UC was lower. Finally, the use of genetic risk scores based on previous GWAS findings reached area under the curves > 0.68. In conclusion, we report on the genetic architecture of IBD in the Basque population, and explore the performance of European-descent genetic risk scores in this population.