An integrative study of genetic variants with brain tissue expression identifies viral etiology and potential drug targets of multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disorder leading to chronic disability. Brain lesions in MS commonly arise in normal-appearing white matter (NAWM). Genome-wide association studies (GWAS) have identified genetic variants associated with MS. Transcriptome alterations have been observed in case-control studies of NAWM. We developed a Cross-Dataset Evaluation (CDE) function for our network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS). We applied CDE to integrate publicly available MS GWAS summary statistics of 41,505 cases and controls with collectively 38 NAWM expression samples, using the human protein interactome as the reference network, to investigate biological underpinnings of MS etiology. We validated the resulting modules with colocalization of GWAS and expression quantitative trait loci (eQTL) signals, using GTEx Consortium expression data for MS-relevant tissues: 14 brain tissues and 4 immune-related tissues. Other network assessments included a drug target query and functional gene set enrichment analysis. CDE prioritized a MS NAWM network containing 55 unique genes. The gene list was enriched (p-value = 2.34 × 10-7) with GWAS-eQTL colocalized genes: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. The resultant network also included drug signatures of FDA-approved medications. Gene set enrichment analysis revealed the top functional term "intracellular transport of virus", among other viral pathways. We prioritize critical genes from the resultant network: CDK4, IFITM3, MAPK1, MAPK3, METTL12B and PIK3R2. Enriched drug signatures suggest potential drug targets and drug repositioning strategies for MS. Finally, we propose mechanisms of potential MS viral onset, based on prioritized gene set and functional enrichment analysis.

Tissue specific regulation of transcription in endometrium and association with disease.

STUDY QUESTION: Are genetic effects on endometrial gene expression tissue specific and/or associated with reproductive traits and diseases? SUMMARY ANSWER: Analyses of RNA-sequence data and individual genotype data from the endometrium identified novel and disease associated, genetic mechanisms regulating gene expression in the endometrium and showed evidence that these mechanisms are shared across biologically similar tissues. WHAT IS KNOWN ALREADY: The endometrium is a complex tissue vital for female reproduction and is a hypothesized source of cells initiating endometriosis. Understanding genetic regulation specific to, and shared between, tissue types can aid the identification of genes involved in complex genetic diseases. STUDY DESIGN, SIZE, DURATION: RNA-sequence and genotype data from 206 individuals was analysed and results were compared with large publicly available datasets. PARTICIPANTS/MATERIALS, SETTING, METHODS: RNA-sequencing and genotype data from 206 endometrial samples was used to identify the influence of genetic variants on gene expression, via expression quantitative trait loci (eQTL) analysis and to compare these endometrial eQTLs with those in other tissues. To investigate the association between endometrial gene expression regulation and reproductive traits and diseases, we conducted a tissue enrichment analysis, transcriptome-wide association study (TWAS) and summary data-based Mendelian randomisation (SMR) analyses. Transcriptomic data was used to test differential gene expression between women with and without endometriosis. MAIN RESULTS AND THE ROLE OF CHANCE: A tissue enrichment analysis with endometriosis genome-wide association study summary statistics showed that genes surrounding endometriosis risk loci were significantly enriched in reproductive tissues. A total of 444 sentinel cis-eQTLs (P < 2.57 × 10-9) and 30 trans-eQTLs (P < 4.65 × 10-13) were detected, including 327 novel cis-eQTLs in endometrium. A large proportion (85%) of endometrial eQTLs are present in other tissues. Genetic effects on endometrial gene expression were highly correlated with the genetic effects on reproductive (e.g. uterus, ovary) and digestive tissues (e.g. salivary gland, stomach), supporting a shared genetic regulation of gene expression in biologically similar tissues. The TWAS analysis indicated that gene expression at 39 loci is associated with endometriosis, including five known endometriosis risk loci. SMR analyses identified potential target genes pleiotropically or causally associated with reproductive traits and diseases including endometriosis. However, without taking account of genetic variants, a direct comparison between women with and without endometriosis showed no significant difference in endometrial gene expression. LARGE SCALE DATA: The eQTL dataset generated in this study is available at http://reproductivegenomics.com.au/shiny/endo_eqtl_rna/. Additional datasets supporting the conclusions of this article are included within the article and the supplementary information files, or are available on reasonable request. LIMITATIONS, REASONS FOR CAUTION: Data are derived from fresh tissue samples and expression levels are an average of expression from different cell types within the endometrium. Subtle cell-specifc expression changes may not be detected and differences in cell composition between samples and across the menstrual cycle will contribute to sample variability. Power to detect tissue specific eQTLs and differences between women with and without endometriosis was limited by the sample size in this study. The statistical approaches used in this study identify the likely gene targets for specific genetic risk factors, but not the functional mechanism by which changes in gene expression may influence disease risk. WIDER IMPLICATIONS OF THE FINDINGS: Our results identify novel genetic variants that regulate gene expression in endometrium and the majority of these are shared across tissues. This allows analysis with large publicly available datasets to identify targets for female reproductive traits and diseases. Much larger studies will be required to identify genetic regulation of gene expression that will be specific to endometrium. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Health and Medical Research Council (NHMRC) under project grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321, GNT1083405 and GNT1107258. G.W.M is supported by a NHMRC Fellowship (GNT1078399). J.Y is supported by an ARC Fellowship (FT180100186). There are no competing interests.

Characterization of QTL and eQTL controlling early Fusarium graminearum infection and deoxynivalenol levels in a Wuhan 1 x Nyubai doubled haploid wheat population.

BACKGROUND: Fusarium head blight (FHB) is a major disease of cereal crops, caused by the fungal pathogen Fusarium graminearum and related species. Breeding wheat for FHB resistance contributes to increase yields and grain quality and to reduce the use of fungicides. The identification of genes and markers for FHB resistance in different wheat genotypes has nevertheless proven challenging. RESULTS: In this study, early infection by F. graminearum was analyzed in a doubled haploid population derived from the cross of the moderately resistant wheat genotypes Wuhan 1 and Nyubai. Three quantitative trait loci (QTL) were identified: 1AL was associated with lower deoxynivalenol content, and 4BS and 5A were associated with reduced F. graminearum infection at 2 days post inoculation. Early resistance alleles were inherited from Wuhan 1 for QTL 1AL and 4BS and inherited from Nyubai for the 5A QTL. Cis and trans expression QTL (eQTL) were identified using RNA-seq data from infected head samples. Hotspots for trans eQTL were identified in the vicinity of the 1AL and 4BS QTL peaks. Among differentially expressed genes with cis eQTL within the QTL support intervals, nine genes had higher expression associated with FHB early resistance, and four genes had higher expression associated with FHB early susceptibility. CONCLUSIONS: Our analysis of genotype and gene expression data of wheat infected by F. graminearum identified three QTL associated with FHB early resistance, and linked genes with eQTL and differential expression patterns to those QTL. These findings may have applications in breeding wheat for early resistance to FHB.

SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies.

BACKGROUND: Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses. METHODS: We used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs. RESULTS: We found that SNPs reported as eQTLs were more significant in GWAS (higher -log10p) regardless of the tissue specificity of the eQTL. Pan-tissue eQTLs (those reported as eQTLs in multiple tissues) tended to be more significant in the GWAS compared to those reported as eQTL in only one tissue type. eQTL density in the ±5 kb adjacent region of a given SNP was also positively associated with the level of GWAS statistical significance regardless of the eQTL status of the SNP. We found that SNPs located in the regions of high eQTL density were more likely to be located in regulatory elements (transcription factor or miRNA binding sites). When SNPs were stratified by the level of statistical significance, the proportion of eQTLs was positively associated with the mean level of statistical significance in the group. The association curve reaches a plateau around -log10p ≈ 5. The observed associations suggest that quasi-significant SNPs (10- 5 < p < 5 × 10- 8) and SNPs at the genome wide level of statistical significance (p < 5 × 10- 8) may have a similar proportions of risk associated SNPs. CONCLUSIONS: The results of this study indicate that the SNP's eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS.

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

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

Chromosome conformation signatures define predictive markers of inadequate response to methotrexate in early rheumatoid arthritis.

BACKGROUND: There is a pressing need in rheumatoid arthritis (RA) to identify patients who will not respond to first-line disease-modifying anti-rheumatic drugs (DMARD). We explored whether differences in genomic architecture represented by a chromosome conformation signature (CCS) in blood taken from early RA patients before methotrexate (MTX) treatment could assist in identifying non-response to DMARD and, whether there is an association between such a signature and RA specific expression quantitative trait loci (eQTL). METHODS: We looked for the presence of a CCS in blood from early RA patients commencing MTX using chromosome conformation capture by EpiSwitch™. Using blood samples from MTX responders, non-responders and healthy controls, a custom designed biomarker discovery array was refined to a 5-marker CCS that could discriminate between responders and non-responders to MTX. We cross-validated the predictive power of the CCS by generating 150 randomized groups of 59 early RA patients (30 responders and 29 non-responders) before MTX treatment. The CCS was validated using a blinded, independent cohort of 19 early RA patients (9 responders and 10 non-responders). Last, the loci of the CCS markers were mapped to RA-specific eQTL. RESULTS: We identified a 5-marker CCS that could identify, at baseline, responders and non-responders to MTX. The CCS consisted of binary chromosome conformations in the genomic regions of IFNAR1, IL-21R, IL-23, CXCL13 and IL-17A. When tested on a cohort of 59 RA patients, the CCS provided a negative predictive value of 90.0% for MTX response. When tested on a blinded independent validation cohort of 19 early RA patients, the signature demonstrated a true negative response rate of 86 and a 90% sensitivity for detection of non-responders to MTX. Only conformations in responders mapped to RA-specific eQTL. CONCLUSIONS: Here we demonstrate that detection of a CCS in blood in early RA is able to predict inadequate response to MTX with a high degree of accuracy. Our results provide a proof of principle that a priori stratification of response to MTX is possible, offering a mechanism to provide alternative treatments for non-responders to MTX earlier in the course of the disease.

The genetic regulation of transcription in human endometrial tissue.

Study question: Do genetic effects regulate gene expression in human endometrium? Summary answer: This study demonstrated strong genetic effects on endometrial gene expression and some evidence for genetic regulation of gene expression in a menstrual cycle stage-specific manner. What is known already: Genetic effects on expression levels for many genes are tissue specific. Endometrial gene expression varies across menstrual cycle stages and between individuals, but there are limited data on genetic control of expression in endometrium. Study design, size, duration: We analysed genome-wide genotype and gene expression data to map cis expression quantitative trait loci (eQTL) in endometrium. Participants/materials, setting, methods: We recruited 123 women of European ancestry. DNA samples from blood were genotyped on Illumina HumanCoreExome chips. Total RNA was extracted from endometrial tissues. Whole-transcriptome profiles were characterized using Illumina Human HT-12 v4.0 Expression Beadchips. We performed eQTL mapping with ~8 000 000 genotyped and imputed single nucleotide polymorphisms (SNPs) and 12 329 genes. Main results and the role of chance: We identified a total of 18 595 cis SNP-probe associations at a study-wide level of significance (P < 1 × 10-7), which correspond to independent eQTLs for 198 unique genes. The eQTLs with the largest effect in endometrial tissue were rs4902335 for CHURC1 (P = 1.05 × 10-32) and rs147253019 for ZP3 (P = 8.22 × 10-30). We further performed a context-specific eQTL analysis to investigate if genetic effects on gene expression regulation act in a menstrual cycle-specific manner. Interestingly, five cis-eQTLs were identified with a significant stage-by-genotype interaction. The strongest stage interaction was the eQTL for C10ORF33 (PYROXD2) with SNP rs2296438 (P = 2.0 × 10-4), where we observe a 2-fold difference in the average expression levels of heterozygous samples depending on the stage of the menstrual cycle. Large scale data: The summary eQTL results are publicly available to browse or download. Limitations, reasons for caution: A limitation of the present study was the relatively modest sample size. It was not powered to identify trans-eQTLs and larger sample sizes will also be needed to provide better power to detect cis-eQTLs and cycle stage-specific effects, given the substantial changes in expression across the menstrual cycle for many genes. Wider implications of the findings: Identification of endometrial eQTLs provides a platform for better understanding genetic effects on endometriosis risk and other endometrial-related pathologies. Study funding/competing interest(s): Funding for this work was provided by NHMRC Project Grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321 and APP1083405. There are no competing interests.

Disentangling the Role of Melatonin and its Receptor MTNR1B in Type 2 Diabetes: Still a Long Way to Go?

PURPOSE OF REVIEW: Type 2 diabetes (T2D) is a complex genetic metabolic disorder. T2D heritability has been estimated around 40-70%. In the last decade, exponential progress has been made in identifying T2D genetic determinants, through genome-wide association studies (GWAS). Among single-nucleotide polymorphisms mostly associated with T2D risk, rs10830963 is located in the MTNR1B gene, encoding one of the two receptors of melatonin, a neurohormone involved in circadian rhythms. Subsequent studies aiming to disentangle the role of MTNR1B in T2D pathophysiology led to controversies. In this review, we will tackle them and will try to give some directions to get a better view of MTNR1B contribution to T2D pathophysiology. RECENT FINDINGS: Recent studies either based on genetic/genomic analyses, clinical/epidemiology data, functional analyses at rs10830963 locus, insulin secretion assays in response to melatonin (involving or not MTNR1B) or animal model analyses have led to strong controversies at each level of interpretation. We discuss possible caveats in these studies and present ways to go beyond these issues, towards a better understanding of T2D molecular mechanisms, keeping in mind that melatonin is a versatile hormone and regulates many functions via its primary role in the body clock.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions.

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

Shared genetics linking sociability with the brain's default mode network.

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. In the present study, we examined the genetic relationship between sociability and DMN-related resting-state functional magnetic resonance imaging (rs-fMRI) traits. To this end, we used genome-wide association summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N=34,691-342,461). First, we examined global and local genetic correlations between sociability and the rs-fMRI traits. Second, to assess putatively causal relationships between the traits, we conducted bi-directional Mendelian randomisation (MR) analyses. Finally, we prioritised genes influencing both sociability and rs-fMRI traits by combining three methods: gene-expression eQTL MR analyses, the CELLECT framework using single-nucleus RNA-seq data, and network propagation in the context of a protein-protein interaction network. Significant local genetic correlations were found between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the frontal/cingulate and angular/temporal cortices. Sociability affected 12 rs-fMRI traits when allowing for weakly correlated genetic instruments. Combing all three methods for gene prioritisation, we defined 17 highly prioritised genes, with DRD2 and LINGO1 showing the most robust evidence across all analyses. By integrating genetic and transcriptomics data, our gene prioritisation strategy may serve as a blueprint for future studies. The prioritised genes could be explored as potential biomarkers for social dysfunction in the context of neuropsychiatric disorders and as drug target genes.

SVA Regulation of Transposable Element Clustered Transcription within the Major Histocompatibility Complex Genomic Class II Region of the Parkinson's Progression Markers Initiative.

SINE-VNTR-Alu (SVA) retrotransposons can regulate expression quantitative trait loci (eQTL) of coding and noncoding genes including transposable elements (TEs) distributed throughout the human genome. Previously, we reported that expressed SVAs and human leucocyte antigen (HLA) class II genotypes on chromosome 6 were associated significantly with Parkinson's disease (PD). Here, our aim was to follow-up our previous study and evaluate the SVA associations and their regulatory effects on the transcription of TEs within the HLA class II genomic region. We reanalyzed the transcriptome data of peripheral blood cells from the Parkinson's Progression Markers Initiative (PPMI) for 1530 subjects for TE and gene RNAs with publicly available computing packages. Four structurally polymorphic SVAs regulate the transcription of 20 distinct clusters of 235 TE loci represented by LINES (37%), SINES (28%), LTR/ERVs (23%), and ancient transposon DNA elements (12%) that are located in close proximity to HLA genes. The transcribed TEs were mostly short length, with an average size of 389 nucleotides. The numbers, types and profiles of positive and negative regulation of TE transcription varied markedly between the four regulatory SVAs. The expressed SVA and TE RNAs in blood cells appear to be enhancer-like elements that are coordinated differentially in the regulation of HLA class II genes. Future work on the mechanisms underlying their regulation and potential impact is essential for elucidating their roles in normal cellular processes and disease pathogenesis.

Single Nucleotide Polymorphisms (SNPs) in the Shadows: Uncovering their Function in Non-Coding Region of Esophageal Cancer.

Esophageal cancer is a complex disease influenced by genetic and environmental factors. Single nucleotide polymorphisms (SNPs) in non-coding regions of the genome have emerged as crucial contributors to esophageal cancer susceptibility. This review provides a comprehensive overview of the role of SNPs in non-coding regions and their association with esophageal cancer. The accumulation of SNPs in the genome has been implicated in esophageal cancer risk. Various studies have identified specific locations in the genome where SNPs are more likely to occur, suggesting a location-specific response. Chromatin conformational studies have shed light on the localization of SNPs and their impact on gene transcription, posttranscriptional modifications, gene expression regulation, and histone modification. Furthermore, miRNA-related SNPs have been found to play a significant role in esophageal squamous cell carcinoma (ESCC). These SNPs can affect miRNA binding sites, thereby altering target gene regulation and contributing to ESCC development. Additionally, the risk of ESCC has been linked to base excision repair, suggesting that SNPs in this pathway may influence disease susceptibility. Somatic DNA segment alterations and modified expression quantitative trait loci (eQTL) have also been associated with ESCC. These alterations can lead to disrupted gene expression and cellular processes, ultimately contributing to cancer development and progression. Moreover, SNPs have been found to be associated with the long non-coding RNA HOTAIR, which plays a crucial role in ESCC pathogenesis. This review concludes with a discussion of the current and future perspectives in the field of SNPs in non-coding regions and their relevance to esophageal cancer. Understanding the functional implications of these SNPs may lead to the identification of novel therapeutic targets and the development of personalized approaches for esophageal cancer prevention and treatment.

Regulatory SVA retrotransposons and classical HLA genotyped-transcripts associated with Parkinson's disease.

Introduction: Parkinson's disease (PD) is a neurodegenerative and polygenic disorder characterised by the progressive loss of neural dopamine and onset of movement disorders. We previously described eight SINE-VNTR-Alu (SVA) retrotransposon-insertion-polymorphisms (RIPs) located and expressed within the Human Leucocyte Antigen (HLA) genomic region of chromosome 6 that modulate the differential co-expression of 71 different genes including the HLA classical class I and class II genes in a Parkinson's Progression Markers Initiative (PPMI) cohort. Aims and methods: In the present study, we (1) reanalysed the PPMI genomic and transcriptomic sequencing data obtained from whole blood of 1521 individuals (867 cases and 654 controls) to infer the genotypes of the transcripts expressed by eight classical HLA class I and class II genes as well as DRA and the DRB3/4/5 haplotypes, and (2) examined the statistical differences between three different PD subgroups (cases) and healthy controls (HC) for the HLA and SVA transcribed genotypes and inferred haplotypes. Results: Significant differences for 57 expressed HLA alleles (21 HLA class I and 36 HLA class II alleles) up to the three-field resolution and four of eight expressed SVA were detected at p<0.05 by the Fisher's exact test within one or other of three different PD subgroups (750 individuals with PD, 57 prodromes, 60 individuals who had scans without evidence of dopamine deficits [SWEDD]), when compared against a group of 654 HCs within the PPMI cohort and when not corrected by the Bonferroni test for multiple comparisons. Fourteen of 20 significant alleles were unique to the PD-HC comparison, whereas 31 of the 57 alleles overlapped between two or more different subgroup comparisons. Only the expressed HLA-DRA*01:01:01 and -DQA1*03:01:01 protective alleles (PD v HC), the -DQA1*03:03:01 risk (HC v Prodrome) or protective allele (PD v Prodrome), the -DRA*01:01:02 and -DRB4*01:03:02 risk alleles (SWEDD v HC), and the NR_SVA_381 present genotype (PD v HC) at a 5% homozygous insertion frequency near HLA-DPA1, were significant (Pc<0.1) after Bonferroni corrections. The homologous NR_SVA_381 insertion significantly decreased the transcription levels of HLA-DPA1 and HLA-DPB1 in the PPMI cohort and its presence as a homozygous genotype is a risk factor (Pc=0.012) for PD. The most frequent NR_SVA_381 insertion haplotype in the PPMI cohort was NR_SVA_381/DPA1*02/DPB1*01 (3.7%). Although HLA C*07/B*07/DRB5*01/DRB1*15/DQB1*06 was the most frequent HLA 5-loci phased-haplotype (n, 76) in the PPMI cohort, the NR_SVA_381 insertion was present in only six of them (8%). Conclusions: These data suggest that expressed SVA and HLA gene alleles in circulating white blood cells are coordinated differentially in the regulation of immune responses and the long-term onset and progression of PD, the mechanisms of which have yet to be elucidated.

Single nucleus RNA-sequencing integrated into risk variant colocalization discovers 17 cell-type-specific abdominal obesity genes for metabolic dysfunction-associated steatotic liver disease.

BACKGROUND: Abdominal obesity increases the risk for non-alcoholic fatty liver disease (NAFLD), now known as metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: To elucidate the directional cell-type level biological mechanisms underlying the association between abdominal obesity and MASLD, we integrated adipose and liver single nucleus RNA-sequencing and bulk cis-expression quantitative trait locus (eQTL) data with the UK Biobank genome-wide association study (GWAS) data using colocalization. Then we used colocalized cis-eQTL variants as instrumental variables in Mendelian randomization (MR) analyses, followed by functional validation experiments on the target genes of the cis-eQTL variants. FINDINGS: We identified 17 colocalized abdominal obesity GWAS variants, regulating 17 adipose cell-type marker genes. Incorporating these 17 variants into MR discovers a putative tissue-of-origin, cell-type-aware causal effect of abdominal obesity on MASLD consistently with multiple MR methods without significant evidence for pleiotropy or heterogeneity. Single cell data confirm the adipocyte-enriched mean expression of the 17 genes. Our cellular experiments across human adipogenesis identify risk variant -specific epigenetic and transcriptional mechanisms. Knocking down two of the 17 genes, PPP2R5A and SH3PXD2B, shows a marked decrease in adipocyte lipidation and significantly alters adipocyte function and adipogenesis regulator genes, including DGAT2, LPL, ADIPOQ, PPARG, and SREBF1. Furthermore, the 17 genes capture a characteristic MASLD expression signature in subcutaneous adipose tissue. INTERPRETATION: Overall, we discover a significant cell-type level effect of abdominal obesity on MASLD and trace its biological effect to adipogenesis. FUNDING: NIH grants R01HG010505, R01DK132775, and R01HL170604; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 802825), Academy of Finland (Grants Nos. 333021), the Finnish Foundation for Cardiovascular Research the Sigrid Jusélius Foundation and the Jane and Aatos Erkko Foundation; American Association for the Study of Liver Diseases (AASLD) Advanced Transplant Hepatology award and NIH/NIDDK (P30DK41301) Pilot and Feasibility award; NIH/NIEHS F32 award (F32ES034668); Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2021), the Academy of Finland grant (Contract no. 138006); Academy of Finland (Grant Nos 335443, 314383, 272376 and 266286), Sigrid Jusélius Foundation, Finnish Medical Foundation, Finnish Diabetes Research Foundation, Novo Nordisk Foundation (#NNF20OC0060547, NNF17OC0027232, NNF10OC1013354) and Government Research Funds to Helsinki University Hospital; Orion Research Foundation, Maud Kuistila Foundation, Finish Medical Foundation, and University of Helsinki.

The Brassica rapa FLC homologue FLC2 is a key regulator of flowering time, identified through transcriptional co-expression networks.

The role of many genes and interactions among genes involved in flowering time have been studied extensively in Arabidopsis, and the purpose of this study was to investigate how effectively results obtained with the model species Arabidopsis can be applied to the Brassicacea with often larger and more complex genomes. Brassica rapa represents a very close relative, with its triplicated genome, with subgenomes having evolved by genome fractionation. The question of whether this genome fractionation is a random process, or whether specific genes are preferentially retained, such as flowering time (Ft) genes that play a role in the extreme morphological variation within the B. rapa species (displayed by the diverse morphotypes), is addressed. Data are presented showing that indeed Ft genes are preferentially retained, so the next intriguing question is whether these different orthologues of Arabidopsis Ft genes play similar roles compared with Arabidopsis, and what is the role of these different orthologues in B. rapa. Using a genetical-genomics approach, co-location of flowering quantitative trait loci (QTLs) and expression QTLs (eQTLs) resulted in identification of candidate genes for flowering QTLs and visualization of co-expression networks of Ft genes and flowering time. A major flowering QTL on A02 at the BrFLC2 locus co-localized with cis eQTLs for BrFLC2, BrSSR1, and BrTCP11, and trans eQTLs for the photoperiod gene BrCO and two paralogues of the floral integrator genes BrSOC1 and BrFT. It is concluded that the BrFLC2 Ft gene is a major regulator of flowering time in the studied doubled haploid population.

Examination of eQTL Polymorphisms Associated with Increased Risk of Progressive Complicated Sarcoidosis in European and African Descent Subjects.

Background: A limited pool of SNPs are linked to the development and severity of sarcoidosis, a systemic granulomatous inflammatory disease. By integrating genome-wide association studies (GWAS) data and expression quantitative trait loci (eQTL) single nuclear polymorphisms (SNPs), we aimed to identify novel sarcoidosis SNPs potentially influencing the development of complicated sarcoidosis. Methods: A GWAS (Affymetrix 6.0) involving 209 African-American (AA) and 193 European-American (EA, 75 and 51 complicated cases respectively) and publicly-available GWAS controls (GAIN) was utilized. Annotation of multi-tissue eQTL SNPs present on the GWAS created a pool of ~46,000 eQTL SNPs examined for association with sarcoidosis risk and severity (Logistic Model, Plink). The most significant EA/AA eQTL SNPs were genotyped in a sarcoidosis validation cohort (n=1034) and cross-validated in two independent GWAS cohorts. Results: No single GWAS SNP achieved significance (p<1x10-8), however, analysis of the eQTL/GWAS SNP pool yielded 621 eQTL SNPs (p<10-4) associated with 730 genes that highlighted innate immunity, MHC Class II, and allograft rejection pathways with multiple SNPs validated in an independent sarcoidosis cohort (105 SNPs analyzed) (NOTCH4, IL27RA, BTNL2, ANXA11, HLA-DRB1). These studies confirm significant association of eQTL/GWAS SNPs in EAs and AAs with sarcoidosis risk and severity (complicated sarcoidosis) involving HLA region and innate immunity. Conclusion: Despite the challenge of deciphering the genetic basis for sarcoidosis risk/severity, these results suggest that integrated eQTL/GWAS approaches may identify novel variants/genes and support the contribution of dysregulated innate immune responses to sarcoidosis severity.

Hidden Genetic Regulation of Human Complex Traits via Brain Isoforms.

Alternative splicing exists in most multi-exonic genes, and exploring these complex alternative splicing events and their resultant isoform expressions is essential. However, it has become conventional that RNA sequencing results have often been summarized into gene-level expression counts mainly due to the multiple ambiguous mapping of reads at highly similar regions. Transcript-level quantification and interpretation are often overlooked, and biological interpretations are often deduced based on combined transcript information at the gene level. Here, for the most variable tissue of alternative splicing, the brain, we estimate isoform expressions in 1,191 samples collected by the Genotype-Tissue Expression (GTEx) Consortium using a powerful method that we previously developed. We perform genome-wide association scans on the isoform ratios per gene and identify isoform-ratio quantitative trait loci (irQTL), which could not be detected by studying gene-level expressions alone. By analyzing the genetic architecture of the irQTL, we show that isoform ratios regulate educational attainment via multiple tissues including the frontal cortex (BA9), cortex, cervical spinal cord, and hippocampus. These tissues are also associated with different neuro-related traits, including Alzheimer's or dementia, mood swings, sleep duration, alcohol intake, intelligence, anxiety or depression, etc. Mendelian randomization (MR) analysis revealed 1,139 pairs of isoforms and neuro-related traits with plausible causal relationships, showing much stronger causal effects than on general diseases measured in the UK Biobank (UKB). Our results highlight essential transcript-level biomarkers in the human brain for neuro-related complex traits and diseases, which could be missed by merely investigating overall gene expressions. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00100-6.

A review of genetic risk in systemic lupus erythematosus.

INTRODUCTION: Systemic Lupus Erythematosus (SLE) is a complex multisystem autoimmune disease with a wide range of signs and symptoms in affected individuals. The utilization of genome-wide association study (GWAS) technology has led to an explosion in the number of genetic risk factors mapped for autoimmune diseases, including SLE. AREAS COVERED: In this review, we summarize the more recent genetic risk loci mapped in SLE, which bring the total number of loci mapped to approximately 200. We review prioritization analyses of the associated variants and experimental validation of the putative causal variants. This includes the implementation of new bioinformatic techniques to align genomic and functional data and the use of transcriptomics with single-cell RNA-sequencing, CRISPR genome editing, and Massive Parallel Reporter Assays to analyze non-coding regulatory genetics. EXPERT OPINION: Despite progress in identifying more genetic risk loci and variant-gene pairs for SLE, understanding its pathogenesis and applying findings clinically remains challenging. The polygenic risk score (PRS) has been used as an application of SLE genetics, but with limited performance in non-EUR populations. In the next few years, advancements in proteomics, post-translational modification estimation, and whole-genome sequencing will enhance disease understanding.

Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders.

Genome-wide association studies reveal the complex polygenic architecture underlying psychiatric disorder risk, but there is an unmet need to validate causal variants, resolve their target genes(s), and explore their functional impacts on disorder-related mechanisms. Disorder-associated loci regulate transcription of target genes in a cell type- and context-specific manner, which can be measured through expression quantitative trait loci. In this review, we discuss methods and insights from context-specific modeling of genetically and environmentally regulated expression. Human induced pluripotent stem cell-derived cell type and organoid models have uncovered context-specific psychiatric disorder associations by investigating tissue-, cell type-, sex-, age-, and stressor-specific genetic regulation of expression. Techniques such as massively parallel reporter assays and pooled CRISPR (clustered regularly interspaced short palindromic repeats) screens make it possible to functionally fine-map genome-wide association study loci and validate their target genes at scale. Integration of disorder-associated contexts with these patient-specific human induced pluripotent stem cell models makes it possible to uncover gene by environment interactions that mediate disorder risk, which will ultimately improve our ability to diagnose and treat psychiatric disorders.

Causal relationship between atrial fibrillation and leukocyte telomere length: A two sample, bidirectional Mendelian randomization study.

Background: Atrial fibrillation (AF) is an age-related disease, while telomeres play a central role in aging. But the relationship between AF and telomere length (LTL) is still controversial. This study aims to examine the potential causal association between AF and LTL by using Mendelian randomization (MR). Methods: Bidirectional two-sample MR, expression and protein quantitative trait loci (eQTL and pQTL)-based MR were performed using genetic variants from United Kingdom Biobank, FinnGen, and a meta-analysis study, which comprised nearly 1 million participants in the Atrial Fibrillation Study and 470,000 participants in the Telomere Length Study. Apart from the inverse variance weighted (IVW) approach as the main MR analysis, complementary analysis approaches and sensitivity analysis were applied. Results: The forward MR revealed a significant causal estimate for the genetically predicted AF with LTL shortening [IVW: odds ratio (OR) = 0.989, p = 0.007; eQTL-IVW: OR = 0.988, p = 0.005; pQTL-IVW: OR = 0.975, p < 0.005]. But in the reverse MR analysis, genetically predicted LTL has no significant correlation with AF (IVW: OR = 0.995, p = 0.916; eQTL-IVW: OR = 0.999, p = 0.995; pQTL-IVW: OR = 1.055, p = 0.570). The FinnGen replication data yielded similar findings. Sensitivity analysis ensured the stability of the results. Conclusion: The presence of AF leads to LTL shortening rather than the other way around. Aggressive intervention for AF may delay the telomere attrition.