Digital Otoscopy With Computer-Aided Composite Image Generation: Impact on the Correct Diagnosis, Confidence, and Time.

OBJECTIVE: This study investigated the comparative performance of ear, nose, and throat (ENT) physicians in correctly detecting ear abnormalities when reviewing digital otoscopy imaging using 3 different visualization methods, including computer-assisted composite images called "SelectStitch," single video frame "Still" images, and video clips. The study also explored clinicians' diagnostic confidence levels and the time to make a diagnosis. STUDY DESIGN: Clinician diagnostic reader study. SETTING: Online diagnostic survey of ENT physicians. METHODS: Nine ENT physicians reviewed digital otoscopy examinations from 86 ears with various diagnoses (normal, perforation, retraction, middle ear effusion, tympanosclerosis). Otoscopy examinations used artificial-intelligence (AI)-based computer-aided composite image generation from a video clip (SelectStitch), manually selected best still frame from a video clip (Still), or the entire video clip. Statistical analyses included comparisons of ability to detect correct diagnosis, confidence levels, and diagnosis times. RESULTS: The ENT physicians' ability to detect ear abnormalities (33.2%-68.7%) varied depending on the pathologies. SelectStitch and Still images were not statistically different in detecting abnormalities (P > .50), but both were different from Video (P < .01). However, the performance improvement observed with Videos came at the cost of significantly longer time to determining the diagnosis. The level of confidence in the diagnosis was positively associated with correct diagnoses, but varied by particular pathology. CONCLUSION: This study explores the potential of computer-assisted techniques like SelectStitch in enhancing otoscopic diagnoses and time-saving, which could benefit telemedicine settings. Comparable performance between computer-generated and manually selected images suggests the potential of AI algorithms for otoscopy applications.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus.

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (encoded by IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKε. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a regulatory pathway involving rs2297550, Ikaros, and IKKε implicated by human genetics in risk for SLE.

Metaboepigenetic regulation of gene expression in obesity and insulin resistance.

INTRODUCTION: Variation in DNA methylation (DNAm) in adipose tissue is associated with the pathogenesis of obesity and insulin resistance. The activity of enzymes involved in altering DNAm levels is dependent on several metabolite cofactors. OBJECTIVES: To understand the role of metabolites as mechanistic regulators of epigenetic marks, we tested the association between selected plasma metabolites and DNAm levels in the adipose tissue of African Americans. METHODS: In the AAGMEx cohort (N = 256), plasma levels of metabolites were measured by untargeted liquid chromatography-mass spectrometry; adipose tissue DNAm and transcript levels were measured by reduced representation bisulfite sequencing, and expression microarray, respectively. RESULTS: Among the 21 one-carbon metabolism pathway metabolites evaluated, six were associated with gluco-metabolic traits (PFDR < 0.05, for BMI, SI, or Matsuda index) in AAGMEx. Methylation levels of 196, 116, and 180 CpG-sites were associated (P < 0.0001) with S-adenosylhomocysteine (SAH), cystine, and hypotaurine, respectively. Cis-expression quantitative trait methylation (cis eQTM) analyses suggested the role of metabolite-level-associated CpG sites in regulating the expression of adipose tissue transcripts, including genes in G-protein coupled receptor signaling pathway. Plasma SAH level-associated CpG sites chr19:3403712 and chr19:3403735 were also associated with the expression of G-protein subunit alpha 15 (GNA15) in adipose. The expression of GNA15 was significantly correlated with BMI (ß = 1.87, P = 1.9 × 10-16) and SI (ß = -1.61, P = 2.49 × 10-5). CONCLUSION: Our study suggests that a subset of metabolites modulates the methylation levels of CpG sites in specific loci and, in turn, regulates the expression of transcripts involved in obesity and insulin resistance.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms.

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

A cis-regulatory element regulates ERAP2 expression through autoimmune disease risk SNPs.

Single-nucleotide polymorphisms (SNPs) near the ERAP2 gene are associated with various autoimmune conditions, as well as protection against lethal infections. Due to high linkage disequilibrium, numerous trait-associated SNPs are correlated with ERAP2 expression; however, their functional mechanisms remain unidentified. We show by reciprocal allelic replacement that ERAP2 expression is directly controlled by the splice region variant rs2248374. However, disease-associated variants in the downstream LNPEP gene promoter are independently associated with ERAP2 expression. Allele-specific conformation capture assays revealed long-range chromatin contacts between the gene promoters of LNPEP and ERAP2 and showed that interactions were stronger in patients carrying the alleles that increase susceptibility to autoimmune diseases. Replacing the SNPs in the LNPEP promoter by reference sequences lowered ERAP2 expression. These findings show that multiple SNPs act in concert to regulate ERAP2 expression and that disease-associated variants can convert a gene promoter region into a potent enhancer of a distal gene.

Deep Resequencing of the 1q22 Locus in Non-Lobar Intracerebral Hemorrhage.

OBJECTIVE: Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases, including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study, we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown. METHODS: A total of 95,000 base pairs spanning 1q22, including SEMA4A, SLC25A44, and PMF1/PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and Rare Variant Influential Filtering Tool analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, chromatin immunoprecipitation followed by sequencing, and chromatin interaction analysis with paired-end tag databases. Multivariable Mendelian randomization assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk. RESULTS: Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop, and that the genes therein belong to the same topologically associating domain. Chromatin immunoprecipitation followed by sequencing and chromatin interaction analysis with paired-end tag data analysis highlighted the presence of long-range interactions between the SEMA4A-promoter and PMF1-enhancer regions prioritized by association testing. Multivariable Mendelian randomization analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk. INTERPRETATION: Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22, offering a potential new target for prevention of ICH and cerebral small vessel disease. ANN NEUROL 2024;95:325-337.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus.

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKϵ. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.

A Novel Metastatic Estrogen Receptor-Expressing Breast Cancer Model with Antiestrogen Responsiveness.

Most women diagnosed with breast cancer (BC) have estrogen receptor alpha-positive (ER+) disease. The current mouse models of ER+ BC often rely on exogenous estrogen to encourage metastasis, which modifies the immune system and the function of some tissues like bone. Other studies use genetically modified or immunocompromised mouse strains, which do not accurately replicate the clinical disease. To create a model of antiestrogen responsive BC with spontaneous metastasis, we developed a mouse model of 4T1.2 triple-negative (TN) breast cancer with virally transduced ER expression that metastasizes spontaneously without exogenous estrogen stimulation and is responsive to antiestrogen drugs. Our mouse model exhibited upregulated ER-responsive genes and multi-organ metastasis without exogenous estrogen administration. Additionally, we developed a second TN BC cell line, E0771/bone, to express ER, and while it expressed ER-responsive genes, it lacked spontaneous metastasis to clinically important tissues. Following antiestrogen treatment (tamoxifen, ICI 182,780, or vehicle control), 4T1.2- and E0771/bone-derived tumor volumes and weights were significantly decreased, exemplifying antiestrogen responsivity in both cell lines. This 4T1.2 tumor model, which expresses the estrogen receptor, metastasizes spontaneously, and responds to antiestrogen treatment, will allow for further investigation into the biology and potential treatment of metastasis.

Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant.

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.

Maternal health and pregnancy outcomes in autosomal dominant tubulointerstitial kidney disease.

Introduction: Autosomal dominant tubulointerstitial kidney disease (ADTKD) is an increasingly recognized cause of chronic kidney disease. ADTKD pregnancy outcomes have not previously been described. Methods: A cross-sectional survey was sent to women from ADTKD families. Results: Information was obtained from 85 afffected women (164 term pregnancies) and 23 controls (50 pregnancies). Only 16.5% of genetically affected women knew they had ADTKD during pregnancy. Eighteen percent of ADTKD mothers had hypertension during pregnancy versus 12% in controls (p = 0.54) and >40% in comparative studies of chronic kidney disease in pregnancy. Eleven percent of births of ADTKD mothers were <37 weeks versus 0 in controls (p < 0.0001). Cesarean section occurred in 19% of pregnancies in affected women versus 38% of unaffected individuals (p = 0.06). Only 12% of babies required a neonatal intensive care unit stay. Conclusions: ADTKD pregnancies had lower rates of hypertension during pregnancy versus other forms of chronic kidney disease, which may have contributed to good maternal and fetal outcomes.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification.

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Genome-wide association study identifies multiple HLA loci for sarcoidosis susceptibility.

Sarcoidosis is a complex systemic disease. Our study aimed to (1) identify novel alleles associated with sarcoidosis susceptibility; (2) provide an in-depth evaluation of HLA alleles and sarcoidosis susceptibility and (3) integrate genetic and transcription data to identify risk loci that may more directly impact disease pathogenesis. We report a genome-wide association study of 1335 sarcoidosis cases and 1264 controls of European descent (EA) and investigate associated alleles in a study of African Americans (AA: 1487 cases and 1504 controls). The EA and AA cohort was recruited from multiple United States sites. HLA alleles were imputed and tested for association with sarcoidosis susceptibility. Expression quantitative locus and colocalization analysis were performed using a subset of subjects with transcriptome data. Forty-nine SNPs in the HLA region in HLA-DRA, -DRB9, -DRB5, -DQA1 and BRD2 genes were significantly associated with sarcoidosis susceptibility in EA, rs3129888 was also a risk variant for sarcoidosis in AA. Classical HLA alleles DRB1*0101, DQA1*0101 and DQB1*0501, which are highly correlated, were also associated with sarcoidosis. rs3135287 near HLA-DRA was associated with HLA-DRA expression in peripheral blood mononuclear cells and bronchoalveolar lavage from subjects and lung tissue and whole blood from GTEx. We identified six novel SNPs (out of the seven SNPs representing the 49 significant SNPs) and nine HLA alleles associated with sarcoidosis susceptibility in the largest EA population. We also replicated our findings in an AA population. Our study reiterates the potential role of antigen recognition and/or presentation HLA class II genes in sarcoidosis pathogenesis.

Validation of Epigenetic Markers for the Prediction of Response to Topical Corticosteroid Treatment in Eosinophilic Esophagitis.

INTRODUCTION: We previously identified 18 CpG methylation biomarkers associated with treatment response to topical corticosteroids (tCS) in eosinophilic esophagitis (EoE). In this study, in an independent cohort, we assessed the validity of these CpG sites as treatment response biomarkers. METHODS: DNA was extracted from prospectively biobanked esophageal biopsies from patients with newly diagnosed EoE enrolled in a randomized trial of 2 tCS formulations. Histologic response was defined as <15 eosinophils per high-power field. Pretreatment DNA methylation was assayed on the Illumina Human MethylationEPIC BeadChip. Logistic regression and area under the receiver operating characteristic curve analyses, adjusting for chip, position on the chip, age, sex, and baseline eosinophil count, were computed to test for an association between DNA methylation and treatment response at the 18 previously identified CpG sites. RESULTS: We analyzed 88 patients (58 histologic responders, 30 nonresponders), with a mean age of 38 ± 16 years, 64% male, 97% White race. Of the 18 CpG sites, 13 met quality control criteria, and 3 were associated with responder status ( P < 0.012), including sites within UNC5B (cg26152017), ITGA6 (cg01044293), and LRRC8A (cg13962589). All 3 showed evidence of reduced methylation in treatment responders, consistent with the original discovery associations. The predictive probability for nonresponse with all 3 CpG sites was strong (area under the receiver operating characteristic curve = 0.79). DISCUSSION: We validated epigenetic biomarkers (CpG methylation sites) for the prediction of tCS response in patients with EoE in an independent population. While not all previously identified markers replicated, 3 demonstrated a relatively high predictive probability for response to treatment and hold promise for guiding tCS treatment in EoE.

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures.

ABSTRACT: Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

Social Determinants of Health and Cerebral Small Vessel Disease: Is Epigenetics a Key Mediator?

Cerebral small vessel disease is highly prevalent, particularly in marginalized communities, and its incidence is expected to increase given the aging global population. Cerebral small vessel disease contributes to risk for stroke, vascular cognitive impairment and dementia, late-life depression, and gait disorders. A growing body of evidence suggests that adverse outcomes, including cerebral small vessel disease, caused by traditional cardiovascular risk factors are at least partly mediated by epigenetic changes, some of them already beginning during fetal development. Societal and health care access inequities, summarized under the umbrella term social determinants of health, put a higher burden of cardiovascular risk factors on marginalized populations and expose them to an increased risk for adverse outcomes. Social epigenetics has begun to deliver solid evidence that social determinants of health lead to distinct epigenetic signatures that potentially mediate the biological effect of environmental exposures on cardiovascular risk factors. Here, we provide a review of the most recent advances in the epigenetics of cerebral small vessel disease risk factors and social determinants of health and call for research efforts combining insights from both fields to reach a deeper understanding of the causal pathways, ultimately facilitating discovery of new treatment targets for a disease whose burden is magnified by existing health disparities.

Identification of influential rare variants in aggregate testing using random forest importance measures.

Aggregate tests of rare variants are often employed to identify associated regions compared to sequentially testing each individual variant. When an aggregate test is significant, it is of interest to identify which rare variants are "driving" the association. We recently developed the rare variant influential filtering tool (RIFT) to identify influential rare variants and showed RIFT had higher true positive rates compared to other published methods. Here we use importance measures from the standard random forest (RF) and variable importance weighted RF (vi-RF) to identify influential variants. For very rare variants (minor allele frequency [MAF] < 0.001), the vi-RF:Accuracy method had the highest median true positive rate (TPR = 0.24; interquartile range [IQR]: 0.13, 0.42) followed by the RF:Accuracy method (TPR = 0.16; IQR: 0.07, 0.33) and both were superior to RIFT (TPR = 0.05; IQR: 0.02, 0.15). Among uncommon variants (0.001 < MAF < 0.03), the RF methods had higher true positive rates than RIFT while observing comparable false positive rates. Finally, we applied the RF methods to a targeted resequencing study in idiopathic pulmonary fibrosis (IPF), in which the vi-RF approach identified eight and seven variants in TERT and FAM13A, respectively. In summary, the vi-RF provides an improved, objective approach to identifying influential variants following a significant aggregate test. We have expanded our previously developed R package RIFT to include the random forest methods.

Deep resequencing of the 1q22 locus in non-lobar intracerebral hemorrhage.

Objective: Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases (CSVDs), including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown. Methods: 95,000 base pairs spanning 1q22 , including SEMA4A, SLC25A44 and PMF1 / PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and RIFT analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, ChIP-Seq and ChIA-PET databases. Multivariable Mendelian randomization (MVMR) assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk. Results: Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop and that the genes therein belong to the same Topologically Associating Domain. ChIP-Seq and ChIA-PET data analysis highlighted the presence of long-range interactions between the SEMA4A -promoter and PMF1 -enhancer regions prioritized by association testing. MVMR analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk. Interpretation: Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22 , offering a potential new target for prevention of ICH and CSVD.

Molecular pathways identified from single nucleotide polymorphisms demonstrate mechanistic differences in systemic lupus erythematosus patients of Asian and European ancestry.

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.