Biology subjects

Terao, C.

Publications and source records attributed to Terao, C..

At least 19 recordsLinked to original sources

bioRxiv2025

Cellular and molecular fine mapping pinpoints new immunopathology of lupus

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with an unknown etiology. To pinpoint new disease-relevant cell states and their molecular profiles, we performed an in-depth investigation of multimodal single-cell datasets comprising [~]2.1 million peripheral blood mononuclear cells from 346 donors. By resolving 123 fine-grained cell states across 27 cell types, we identified previously uncharacterized populations distinctively associated with clinical severity and treatment status, including GZMK+GZMH+HLA-DR+ effector memory CD8+ T cells (double-positive [DP] EMCD8) and FOXO1+ARHGAP15+ T cells. Through extensive statistical frameworks and multimodal approaches, we delineated their aberrant immune signaling networks, transcriptional regulators, key surface proteins, T cell receptor repertoires, and genetic/epigenetic landscapes, underscoring them as candidate drivers of SLE immunopathology. These findings provide new insights into therapeutic target discovery in SLE.

immunology↗

bioRxiv2024

Predicted constrained accessible regions mark regulatory elements and causal variants

Open chromatin regions (OCRs) define cell-type-specific regulatory elements across the genome, yet their functional significance varies, making it challenging to pinpoint biologically essential regions. Here, we introduce CAMBUS (Chromatin Accessibility Mutation Burden Score), a machine-learning framework that identifies active and evolutionarily constrained OCRs by leveraging surrounding DNA sequences. Applying CAMBUS to 29 immune cell types, we identified 66,043 constrained OCRs, which were substantially enriched in the known constraint genome (odds ratio=11.45 (95% confidence interval 9.33-14.05), P=4.7 x 10-68), while 90% of these OCRs were not prioritized by existing constraint metrics. These OCRs were highly enriched for known enhancers and super-enhancers, independent of known epigenetic markers and annotated regions, and overlapped with regulatory elements implicated in immune-mediated diseases and experimentally validated functional variants, including rare variants, particularly in leukocyte-related traits. Furthermore, CAMBUS revealed cell-type-specific transcriptional regulatory landscapes, linking genetic constraint with gene regulation in immune cells and identifying plausible connections between 1,533 causal variants and 70 complex traits. By defining biologically constrained regulatory elements at high resolution, CAMBUS provides a framework for understanding the selective pressures shaping the non-coding genome and its role in human health and disease.

genetics↗

bioRxiv2024

Impaired central pattern generators due to abnormal EPHA4 signaling leads to idiopathic scoliosis

Idiopathic scoliosis (IS) is the most common form of spinal deformity with unclear pathogenesis. In this study, we firstly reanalyzed the loci associated with IS, drawing upon previous studies. Subsequently, we mapped these loci to candidate genes using either location-based or function-based strategies. To further substantiate our findings, we verified the enrichment of variants within these candidate genes across several large IS cohorts encompassing Chinese, East Asian, and European populations. Consequently, we identified variants in the EPHA4 gene as compelling candidates for IS. To confirm their pathogenicity, we generated zebrafish mutants of epha4a. Remarkably, the zebrafish epha4a mutants exhibited pronounced scoliosis during later stages of development, effectively recapitulating the IS phenotype. We observed that the epha4a mutants displayed defects in left-right coordination during locomotion, which arose from disorganized neural activation in these mutants. Our subsequent experiments indicated that the disruption of the central pattern generator (CPG) network, characterized by abnormal axon guidance of spinal cord interneurons, contributed to the disorganization observed in the mutants. Moreover, when knocked down efnb3b, the ligand for Epha4a, we observed similar CPG defects and disrupted left-right locomotion. These findings strongly suggested that ephrin B3-Epha4 signaling is vital for the proper functioning of CPGs, and defects in this pathway could lead to scoliosis in zebrafish. Furthermore, we identified two cases of IS in NGEF, a downstream molecule in the EPHA4 pathway. Collectively, our data provide compelling evidence that neural patterning impairments and disruptions in CPGs may underlie the pathogenesis of IS.

genetics↗

bioRxiv2023

A single-cell atlas of transcribed cis-regulatory elements in the human genome

Transcribed cis-regulatory elements (tCREs), such as promoters and enhancers, are fundamental to modulate gene expression and define cell identity. The detailed mapping of tCREs at single-cell resolution is essential for understanding the regulatory mechanisms that govern cellular functions. Prior tCRE catalogs, limited by bulk analysis, have often overlooked cellular heterogeneity. We have constructed a tCRE atlas using single-cell 5-RNA-seq, capturing over 340,000 single-cells from 23 human tissues and annotating more than 175,000 tCREs, substantially enhancing the scope and granularity of existing cis-regulatory element annotations in the human genome. This atlas unveils patterns of gene regulation, revealing connections between broadly expressed promoters and cell type-specific distal tCREs. Assessing trait heritability at single-cell resolution with a novel tCRE module-based approach, we uncovered the nuanced trait-gene regulatory relationships across a continuum of cell populations, offering insights beyond traditional gene-level and bulk-sample analyses. Our study bridges the gap between gene regulation and trait heritability, underscoring the potential of single-cell analysis to elucidate the genetic foundations of complex traits. These insights set the stage for future research to investigate the impact of genetic variations on diseases at the individual level, advancing the understanding of cellular and molecular basis of trait heritability.

genomics↗

bioRxiv2023

Hidden protein-altering variants influence diverse human phenotypes

Structural variants (SVs) comprise the largest genetic variants, altering from 50 base pairs to megabases of DNA. However, SVs have not been effectively ascertained in most genetic association studies, leaving a key gap in our understanding of human complex trait genetics. We ascertained protein-altering SVs from UK Biobank whole-exome sequencing data (n=468,570) using haplotype-informed methods capable of detecting sub-exonic SVs and variation within segmental duplications. Incorporating SVs into analyses of rare variants predicted to cause gene loss-of-function (pLoF) identified 100 associations of pLoF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 appeared to confer one of the strongest protective effects of gene LoF on hypertension risk (OR = 0.86 [0.82-0.90]). Protein-coding variation in rapidly-evolving gene families within segmental duplications--previously invisible to most analysis methods--appeared to generate some of the human genomes largest contributions to variation in type 2 diabetes risk, chronotype, and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.

genetics↗

bioRxiv2023

Characterizing the quality metric in genotype imputation

Large-scale imputation reference panels are now available and have contributed to efficient genome-wide association studies through genotype imputation. However, it is still under debate whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations. We imputed genotypes of East Asian (EAS; 180k Japanese) subjects using the Trans-Omics for Precision Medicine (TOPMed) reference panel and found that the standard imputation quality metric (Rsq) substantially overestimated the dosage r2 (squared correlation between imputed dosage and true genotype). Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1, or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates ({theta} value) in the hidden Markov model, we uncovered that the lower {theta} value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the {theta} value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the {theta} value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could overestimate or underestimate dosage r2 for a subpopulation in the multi-ancestry panel and the deviation represents different imputed-dosage distributions. Finally, despite the impact of {theta} value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the {theta} value has a substantial impact on the imputed dosage and the imputation quality metric value.

bioinformatics↗

bioRxiv2023

Association of an estrogen-sensitive Pax1-Col11a1-Mmp3 signaling axis with adolescent idiopathic scoliosis

Adolescent idiopathic scoliosis (AIS) is a common and progressive spinal deformity in children that exhibits striking sexual dimorphism, with girls at more than five-fold greater risk of severe disease compared to boys. Despite its medical impact, the molecular mechanisms that drive AIS are largely unknown. We previously defined a female-specific AIS genetic risk locus in an enhancer near the PAX1 gene. Here we sought to define the roles of PAX1 and newly-identified AIS-associated genes in the developmental mechanism of AIS. In a genetic study of 10,519 individuals with AIS and 93,238 unaffected controls, significant association was identified with a variant in COL11A1 encoding collagen (1) XI (rs3753841; NM_080629.2_c.4004C>T; p.(Pro1335Leu); P=7.07e-11, OR=1.118). Using CRISPR mutagenesis we generated Pax1 knockout mice (Pax1-/-). In postnatal spines we found that PAX1 and collagen (1) XI protein both localize within the intervertebral disc (IVD)-vertebral junction region encompassing the growth plate, with less collagen (1) XI detected in Pax1-/- spines compared to wildtype. By genetic targeting we found that wildtype Col11a1 expression in costal chondrocytes suppresses expression of Pax1 and of Mmp3, encoding the matrix metalloproteinase 3 enzyme implicated in matrix remodeling. However, this suppression was abrogated in the presence of the AIS-associated COL11A1P1335L mutant. Further, we found that either knockdown of the estrogen receptor gene Esr2, or tamoxifen treatment, significantly altered Col11a1 and Mmp3 expression in chondrocytes. We propose a new molecular model of AIS pathogenesis wherein genetic variation and estrogen signaling increase disease susceptibility by altering a Pax1-Col11a1-Mmp3 signaling axis in spinal chondrocytes.

genetics↗

bioRxiv2022

Mobile elements in human population-specific genome and phenotype divergence

Mobile genetic elements (MEs) are heritable mutagens that contribute to divergence between lineages by recursively generating structural variants. ME variants (MEVs) are difficult to genotype, obscuring their impact on recent genome and trait diversification. We developed a tool that uses short-read sequence data to accurately genotype MEVs, enabling us to study them using statistical genetics methods in global human genomes. We observe population-specific differences in the distribution of Alu insertions that distinguish Japanese from other populations. We integrated MEVs with epigenomic and expression quantitative trait loci (eQTL) maps to determine how they impact traits. This reveals coherent patterns by which specific MEs regulate tissue-specific gene expression, including creating or attenuating enhancers and recruiting post-transcriptional regulators. We pinpoint MEVs as genetic causes of disease risk, including a LINE-1 insertion linked to keloid and other diseases of fibroblast inflammation, by introducing MEVs into the genome-wide association study (GWAS) framework. In addition to nominating previously-hidden MEVs as causes of human diseases, this work highlights MEs as accelerators of human population divergence and begins to decipher the semantics of MEs.

genetics↗

bioRxiv2021

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWAS) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations, and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels, and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. Two prioritized genes, CREBRF and RRBP1, show convergent evidence across functional datasets supporting their roles in lipid biology.

genomics↗

bioRxiv2021

Profiling of transcribed cis-regulatory elements in single cells

Profiling of cis-regulatory elements (CREs, mostly promoters and enhancers) in single cells allows the interrogation of the cell-type and cell-state-specific contexts of gene regulation and genetic predisposition to diseases. Here we demonstrate single-cell RNA-5'end-sequencing (sc-end5-seq) methods can detect transcribed CREs (tCREs), enabling simultaneous quantification of gene expression and enhancer activities in a single assay at no extra cost. We showed enhancer RNAs can be detected using sc-end5-seq methods with either random or oligo(dT) priming. To analyze tCREs in single cells, we developed SCAFE (Single Cell Analysis of Five-prime Ends) to identify genuine tCREs and analyze their activities (https://github.com/chung-lab/scafe). As compared to accessible CRE (aCRE, based on chromatin accessibility), tCREs are more accurate in predicting CRE interactions by co-activity, more sensitive in detecting shifts in alternative promoter usage and more enriched in diseases heritability. Our results highlight additional dimensions within sc-end5-seq data which can be used for interrogating gene regulation and disease heritability.

genomics↗

bioRxiv2021

Combined landscape of single-nucleotide variants and copy-number alterations in clonal hematopoiesis

Implicated in the development of hematological malignancies (HM) and cardiovascular mortality, clonal hematopoiesis (CH) in apparently healthy individuals has been investigated by detecting either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here by combining targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in a general population of 11,234 individuals, including 672 with subsequent HM development. Both CH-related lesions significantly co-occurred, which combined, affected blood count, hypertension, and the mortality from HM and cardiovascular diseases depending on the total number of both lesions, highlighting the importance of detecting both lesions in the evaluation of CH.

cancer biology↗

bioRxiv2021

Functional annotation of human long noncoding RNAs using chromatin conformation data

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Studying lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. LncRNAs direct the regulatory factors in the locations that are in cis to their transcription sites. We designed a model to predict if an lncRNA acts in cis based on its features and trained it using RNA-chromatin interaction data. The trained model is cell type-independent and does not require RNA-chromatin data. Combining RNA-chromatin and Hi-C data, we showed that lncRNA-chromatin binding sites are determined by chromosome conformation. For each lncRNA, the spatially proximal genes were identified as their potential targets by combining Hi-C and Cap Analysis Gene Expression (CAGE) data in 18 human cell types. RNA-protein and RNA-chromatin interaction data suggested that lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. We provide the data through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

genomics↗

bioRxiv2020

Predicting cell-type-specific non-coding RNA transcription from genome sequence

Transcription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). However, because transcription of ncRNAs, especially enhancer RNAs, is often low and cell type-specific, its dependency on genotype remains largely unexplored. Here, we developed mutation effect prediction on ncRNA transcription (MENTR), a quantitative machine learning framework reliably connecting genetic associations with expression of ncRNAs, resolved to the level of cell type. MENTR-predicted mutation effects on ncRNA transcription were concordant with estimates from previous genetic studies in a cell type-dependent manner. We inferred reliable causal variants from 41,223 GWAS variants, and proposed 7,775 enhancers and 3,548 long-ncRNAs as complex trait-associated ncRNAs in 348 major human primary cells and tissues, including plausible enhancer-mediated functional alterations in single-variant resolution in Crohns disease. In summary, we present new resources for discovering causal variants, the biological mechanisms driving complex traits, and the sequence-dependency of ncRNA regulation in relevant cell types.

genomics↗

bioRxiv2020

Population-wide Screening for Germline Variants of Hereditary Cancer Genes in 12K Unselected Japanese Colorectal Cancers and 27K Controls

Background & AimsColorectal cancer (CRC) is one of the most common cancers in Western countries and Japan. Currently, a few % of CRCs can be attributed to recognizable hereditary germline variants of known CRC susceptibility genes, predominantly the DNA mismatch repair genes. To establish a universal screening strategy for hereditary CRCs, it is necessary to explore the prevalence of hereditary CRC and pathogenic variants of multiple cancer-predisposing genes in non-European populations. MethodsWe analyzed the coding regions of 27 cancer-predisposing genes, including mismatch repair genes, APC, and BRCA1/2, in 12,503 unselected Japanese CRC patients and 23,705 controls aged [≥] 60 years without any personal or family history of cancer by target sequencing and genome-wide SNP chip data. Their clinical significance was assessed using ClinVar and the guidelines by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). ResultsWe identified 4,804 variants in the 27 genes and annotated them as 397 pathogenic variants, 941 benign variants, and 3,466 variants of uncertain significance, of which 43.6% were registered in neither ClinVar nor dbSNP. In total, 3.3% of the unselected CRC patients and 1.5% of the controls had a pathogenic variant of the 27 genes. The pathogenic variants of MSH2 (odds ratio (OR) =18.1), MLH1 (OR=8.6), MSH6 (OR=4.9), APC (OR=49.4), BRIP1 (OR=3.6), BRCA1 (OR=2.6), BRCA2 (OR=1.9), and TP53 (OR=1.7) were significantly associated with CRC development in the Japanese population (P-values < 0.01, FDR<0.05). Furthermore, we confirmed copy number variants (CNVs) of MSH2/EPCAM, MLH1, and APC by multiplex ligation-dependent probe amplification (MLPA) and quantitative PCR in this cohort (n = 23), including whole gene duplications of MSH2 and APC. These pathogenic variants were significantly associated with the diagnostic age and personal/family history of other types of cancer. In total, at least 3.5% of the Japanese CRC population had a pathogenic variant or CNV of the 27 cancer-predisposing genes. ConclusionsThis is the largest study of CRC heredity in the Asian population and would contribute to the development of guidelines for genetic testing and variant interpretation for heritable CRCs. Universal screening for CRC risk should be assessed in multiple genes, including BRCA1/2 and BRIP1. These data would facilitate risk assessment of cancer and optimize the screening strategy.

genetics↗

bioRxiv2020

In silico integration of thousands of epigenetic datasets into 707 cell type regulatory annotations improves the trans-ethnic portability of polygenic risk scores

Poor trans-ethnic portability of polygenic risk score (PRS) models is a critical issue that may be partially due to limited knowledge of causal variants shared among populations. Hence, leveraging noncoding regulatory annotations that capture genetic variation across populations has the potential to enhance the trans-ethnic portability of PRS. To this end, we constructed a unique resource of 707 cell-type-specific IMPACT regulatory annotations by aggregating 5,345 public epigenetic datasets to predict binding patterns of 142 cell-type-regulating transcription factors across 245 cell types. With this resource, we partitioned the common SNP heritability of diverse polygenic traits and diseases from 111 GWAS summary statistics of European (EUR, average N=180K) and East Asian (EAS, average N=157K) origin. For 95 traits, we were able to identify a single IMPACT annotation most strongly enriched for trait heritability. Across traits, these annotations captured an average of 43.3% of heritability (se = 13.8%) with the top 5% of SNPs. Strikingly, we observed highly concordant polygenic trait regulation between populations: the same regulatory annotations captured statistically indistinguishable SNP heritability (fitted slope = 0.98, se = 0.04). Since IMPACT annotations capture both large and consistent proportions of heritability across populations, prioritizing variants in IMPACT regulatory elements may improve the trans-ethnic portability of PRS. Indeed, we observed that EUR PRS models more accurately predicted 21 tested phenotypes of EAS individuals when variants were prioritized by key IMPACT tracks (49.9% mean relative increase in R2). Notably, the improvement afforded by IMPACT was greater in the trans-ethnic EUR-to-EAS PRS application than in the EAS-to-EAS application (47.3% vs 20.9%, P < 1.7e-4). Overall, our study identifies a crucial role for functional annotations such as IMPACT to improve the trans-ethnic portability of genetic data, and this has important implications for future risk prediction models that work across populations.

genetics↗

bioRxiv2019

Endogenization and excision of human herpesvirus 6 in human genomes

The genome of human herpesvirus 6 (HHV-6) is integrated within the nuclear genome of about 1% of humans, but how this came about is not clear. HHV-6 integrates into telomeres, and this has recently been associated with polymorphisms affecting MOV10L1. MOV10L1 is located on the subtelomere of chromosome 22q (chr22q) and is required to make PIWI-interacting RNAs (piRNAs). piRNAs block integration of transposons in the germline, so piRNA-mediated repression of HHV-6 integration has been suspected. Whether integrated HHV-6 can reactive into an infectious virus is also uncertain. In vitro, recombination of the viral genome along its terminal direct repeats (DRs) leads to excision from the telomere and viral reactivation, but the expected single DR "scar" has not been described in vivo. We analyzed whole-genome sequencing (WGS) data from 13,040 subjects, including 7,485 from Japan. We found an association between integrated HHV-6 and polymorphisms on chr22q in Japanese subjects. However, association with the reported MOV10L1 polymorphism was driven by physical linkage to a single ancient endogenous HHV-6A variant integrated into the telomere of chr22q in East Asians. We resolved the junction of the human chromosome with this viral genome using long read sequencing. Unexpectedly, an HHV-6B variant has also endogenized in chr22q; two endogenous HHV-6 variants at this locus thus account for 72% of all integrated HHV-6 in Japan. We also report human genomes carrying only one portion of the HHV-6B genome, a single DR, supporting in vivo excision and viral reactivation. Using WGS data from North American families, we show that the incidence of HHV-6 integration into the germline is lower than its prevalence, and that integrated HHV-6 is not associated with the reported variant in MOV10L1. Together these results explain the recently reported association between integrated HHV-6 and MOV10L1/piRNAs, suggest exaptation of HHV-6 in its coevolution with human chr22q, and clarify the evolution and risk of reactivation of the only intact non-retroviral genome known to be present in human germlines. SIGNIFICANCE STATEMENT Human herpesvirus 6 (HHV-6) infects most people during childhood, usually only causing fever and rash. Reactivation of HHV-6 has been linked to a number of neurological diseases including encephalitis, Alzheimers disease and multiple sclerosis. However, about 1% of people are born with the HHV-6 genome present within their genome, included in the end "cap" of one of their 46 chromosomes. Little is known about how and when HHV-6 genomes entered human genomes, whether or not they still do, and whether or not this poses risk for virus reactivation. We looked for HHV-6 in genome sequences from over 13,000 people. Most HHV-6 variants present in human genomes have been co-evolving with human chromosomes for many generations, and new integration events are rare. Surprisingly, in almost three fourths of Japanese people with HHV-6 in their genome, HHV-6 integrated in the same end of the same chromosome - 22q. Persistence of the HHV-6 genome within the short "cap" that preserves the end of chromosome 22q suggests that the integrated viral sequence may have taken on a useful function for this chromosome. We also found that some human genomes harbor only one part of the HHV-6 genome. This part is the same part that remains after experimental viral reactivation, during which most of the virus is cut out of the genome. This warrants assessment of the risk that integration of HHV-6 into inherited human genomes is not irreversible, and possibly leads to production of infectious virus.

genetics↗

bioRxiv2019

Population-specific and transethnic genome-wide analyses reveal distinct and shared genetic risks of coronary artery disease

To elucidate the genetics of coronary artery disease (CAD) in the Japanese population, we conducted a large-scale genome-wide association study (GWAS) of 168,228 Japanese (25,892 cases and 142,336 controls) with genotype imputation using a newly developed reference panel of Japanese haplotypes including 1,782 CAD cases and 3,148 controls. We detected 9 novel disease-susceptibility loci and Japanese-specific rare variants contributing to disease severity and increased cardiovascular mortality. We then conducted a transethnic meta-analysis and discovered 37 additional novel loci. Using the result of the meta-analysis, we derived a polygenic risk score (PRS) for CAD, which outperformed those derived from either Japanese or European GWAS. The PRS prioritized risk factors among various clinical parameters and segregated individuals with increased risk of long-term cardiovascular mortality. Our data improves clinical characterization of CAD genetics and suggests the utility of transethnic meta-analysis for PRS derivation in non-European populations.

genetics↗

bioRxiv2019

Using genetics to differentiate patients with similar symptoms: application to inflammatory arthritis in the rheumatology outpatient clinic

Slow developing complex diseases are a clinical diagnostic challenge. Since genetic information is increasingly available prior to a patients first visit to a clinic, it might improve diagnostic accuracy. We aimed to devise a method to convert genetic information into simple probabilities discriminating between multiple diagnoses in patients presenting with inflammatory arthritis.\n\nWe developed G-Prob, which calculates for each patient the genetic probability for each of multiple possible diseases. We tested this for inflammatory arthritis-causing diseases (rheumatoid arthritis, systemic lupus erythematosus, spondyloarthropathy, psoriatic arthritis and gout). After validating in simulated data, we tested G-Prob in biobank cohorts in which genetic data were linked to electronic medical records: - 1,200 patients identified by ICD-codes within the eMERGE database (n= 52,623);\n- 245 patients identified through ICD codes and review of medical records within the Partners Biobank (n=12,604);\n- 243 patients selected prospectively with final diagnoses by medical record review within the Partners Biobank (n=12,604).\nThe calibration of G-Prob with the disease status was high (with regression coefficients ranging from 0.90-1.08 (ideal would be 1.00) in all cohorts. G-Probs discriminative ability was high in all cohorts with pooled Area Under the Curve (AUC)=0.69 [95%CI 0.67-0.71], 0.81 [95%CI 0.76-0.84] and 0.84 [95%CI 0.81-0.86]. For all patients, at least one disease could be ruled out, and in 45% of patients a most likely diagnosis could be identified with an overall 64% positive predictive value. In 35% of instances the clinicians initial diagnosis was incorrect. Initial clinical diagnosis explained 39% of the variance in final disease prediction which improved to 51% (P<0.0001) by adding G-Prob genetic data.\n\nIn conclusion, by converting genotypes into an interpretable probability value for five different inflammatory arthritides, we can better discriminate and diagnose rheumatic diseases. Genotypes available prior to a clinical visit could be considered part of patients medical history and potentially used to improve precision and diagnostic efficiency in clinical practice.

genetics↗