Pleiotropic variants (i.e. genetic polymorphisms influencing more than one phenotype) are often associated with cancer risk. A scan of pleiotropic variants was successfully conducted 10 years ago in relation to pancreatic ductal adenocarcinoma susceptibility. However, in the last decade, genetic association studies performed on several human traits have greatly increased the number of known pleiotropic variants. Based on the hypothesis that variants already associated with a least one trait have a higher probability of association with other traits, 61 052 variants reported to be associated by at least one genome-wide association study with at least one human trait were tested in the present study consisting of two phases (discovery and validation), comprising a total of 16 055 pancreatic ductal adenocarcinoma (PDAC) cases and 212 149 controls. The meta-analysis of the two phases showed two loci (10q21.1-rs4948550 (P = 6.52 × 10-5) and 7q36.3-rs288762 (P = 3.03 × 10-5) potentially associated with PDAC risk. 10q21.1-rs4948550 shows a high degree of pleiotropy and it is also associated with colorectal cancer risk while 7q36.3-rs288762 is situated 28,558 base pairs upstream of the Sonic Hedgehog (SHH) gene, which is involved in the cell-differentiation process and PDAC etiopathogenesis. In conclusion, none of the single nucleotide polymorphisms (SNPs) showed a formally statistically significant association after correction for multiple testing. However, given their pleiotropic nature and association with various human traits including colorectal cancer, the two SNPs showing the best associations with PDAC risk merit further investigation through fine mapping and ad hoc functional studies.
- MeSH
- Genome-Wide Association Study * MeSH
- Carcinoma, Pancreatic Ductal * genetics MeSH
- Genetic Pleiotropy * MeSH
- Genetic Predisposition to Disease * MeSH
- Polymorphism, Single Nucleotide * MeSH
- Humans MeSH
- Chromosomes, Human, Pair 10 genetics MeSH
- Chromosomes, Human, Pair 7 genetics MeSH
- Pancreatic Neoplasms * genetics MeSH
- Case-Control Studies MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.
Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.
- MeSH
- Asian People genetics MeSH
- White MeSH
- White People genetics MeSH
- Bipolar Disorder * genetics MeSH
- Genome-Wide Association Study * MeSH
- Black or African American genetics MeSH
- Phenotype * MeSH
- GABAergic Neurons metabolism MeSH
- Genetic Predisposition to Disease MeSH
- Genomics * MeSH
- Hispanic or Latino genetics MeSH
- Humans MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.
- MeSH
- B-Lymphocytes immunology metabolism MeSH
- Genome-Wide Association Study * MeSH
- Genetic Predisposition to Disease * MeSH
- Polymorphism, Single Nucleotide * MeSH
- Humans MeSH
- B-Cell Maturation Antigen * genetics MeSH
- Mendelian Randomization Analysis MeSH
- Multiple Myeloma * genetics MeSH
- Transmembrane Activator and CAML Interactor Protein genetics MeSH
- Case-Control Studies MeSH
- Telomere genetics MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.
- MeSH
- Asian People * genetics MeSH
- White People * genetics MeSH
- Genome-Wide Association Study * MeSH
- Genetic Predisposition to Disease * MeSH
- Polymorphism, Single Nucleotide * MeSH
- Colorectal Neoplasms * genetics MeSH
- Humans MeSH
- Quantitative Trait Loci * MeSH
- Chromosome Mapping MeSH
- Exome Sequencing MeSH
- Case-Control Studies MeSH
- Transcriptome MeSH
- East Asian People MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.
- MeSH
- Alzheimer Disease * genetics MeSH
- Histocompatibility Antigens MeSH
- HLA Antigens MeSH
- HLA-DRB1 Chains * genetics MeSH
- Humans MeSH
- Parkinson Disease * genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.
- MeSH
- Autoimmunity genetics MeSH
- Autoimmune Diseases * epidemiology genetics MeSH
- Influenza, Human * epidemiology genetics MeSH
- Humans MeSH
- Narcolepsy * chemically induced genetics MeSH
- Influenza Vaccines * adverse effects MeSH
- Influenza A Virus, H1N1 Subtype * genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
Adaxial, abaxial phylloplane (leaf), and spermoplane (seed) are proximal yet contrasting habitats for a microbiota that needs to be adequately explored. Here, we proposed novel methods to decipher the adaxial/abaxial-phylloplane and spermoplane-microbiomes. Comparison of 22 meta barcoded-NGS datasets (size of total data set-1980.48 Mb) enabled us to fine-map the microbiome of the rice foliar niche, which encompasses the lower, middle, top leaf as well panicle. Here, the total- and the cultivable-microbiome profiling revealed 157 genera representing ten phyla and 87 genera from 4 bacterial phyla, respectively, with a predominance of Proteobacteria and Actinobacteria. Interestingly, more bacterial communities (124-genera) preferred the abaxial than the adaxial phylloplane (104-genera) and spermoplane (67-genera) for colonization. The microbiome profiles were nearly identical on the aromatic (125-genera) and non-aromatic rice (116-genera) with high representation of Pantoea, Methylobacterium, Curtobacterium, Sphingopyxis, and Microbacterium. The culturomics investigation confirmed the abundance of Pantoea, Chryseobacterium, Pseudomonas, Acinetobacter, Sphingobacterium, and Exiguobacterium. One hundred bacterial isolates characterized and identified by polyphasic-taxonomic tools revealed the dominance of Acinetobacter, Chryseobacterium, Enterobacter, Massilia, Pantoea, Pseudomonas, and Stenotrophomonas on adaxial/abaxial-phylloplane and spermoplane. The study culminated in identifying hitherto unexplored bacterial communities on the adaxial/abaxial phylloplane and spermoplane of rice that can be harnessed for microbiome-assisted rice cultivation in the future.
- MeSH
- Genotype MeSH
- Plant Leaves microbiology MeSH
- Microbiota * MeSH
- Oryza * MeSH
- Sphingomonadaceae * MeSH
- Publication type
- Journal Article MeSH
Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations-eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.
- MeSH
- Genome-Wide Association Study * MeSH
- Child MeSH
- Genetic Predisposition to Disease MeSH
- Haplotypes MeSH
- Polymorphism, Single Nucleotide MeSH
- Humans MeSH
- Nephrotic Syndrome * genetics MeSH
- Risk Factors MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
OBJECTIVE: The idiopathic inflammatory myopathies (IIMs) are heterogeneous diseases thought to be initiated by immune activation in genetically predisposed individuals. We imputed variants from the ImmunoChip array using a large reference panel to fine-map associations and identify novel associations in IIM. METHODS: We analyzed 2,565 Caucasian IIM patient samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically matched control samples. We imputed 1,648,116 variants from the ImmunoChip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM and clinical and serologic subgroups. RESULTS: The HLA locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, SDK2 and LINC00924 (both novel) and STAT4 in the whole IIM cohort, with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and for CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells. CONCLUSION: We found novel and strong associations in IIM and PM and localized signals to single genes and immune cell types.
