Narrowing the diagnostic gap: Genomes, episignatures, long-read sequencing, and health economic analyses in an exome-negative intellectual disability cohort.

PURPOSE: Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively. METHODS: ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID. RESULTS: The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis. CONCLUSION: Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost.

Integration of EpiSign, facial phenotyping, and likelihood ratio interpretation of clinical abnormalities in the re-classification of an ARID1B missense variant.

Heterozygous ARID1B variants result in Coffin-Siris syndrome. Features may include hypoplastic nails, slow growth, characteristic facial features, hypotonia, hypertrichosis, and sparse scalp hair. Most reported cases are due to ARID1B loss of function variants. We report a boy with developmental delay, feeding difficulties, aspiration, recurrent respiratory infections, slow growth, and hypotonia without a clinical diagnosis, where a previously unreported ARID1B missense variant was classified as a variant of uncertain significance. The pathogenicity of this variant was refined through combined methodologies including genome-wide methylation signature analysis (EpiSign), Machine Learning (ML) facial phenotyping, and LIRICAL. Trio exome sequencing and EpiSign were performed. ML facial phenotyping compared facial images using FaceMatch and GestaltMatcher to syndrome-specific libraries to prioritize the trio exome bioinformatic pipeline gene list output. Phenotype-driven variant prioritization was performed with LIRICAL. A de novo heterozygous missense variant, ARID1B p.(Tyr1268His), was reported as a variant of uncertain significance. The ACMG classification was refined to likely pathogenic by a supportive methylation signature, ML facial phenotyping, and prioritization through LIRICAL. The ARID1B genotype-phenotype has been expanded through an extended analysis of missense variation through genome-wide methylation signatures, ML facial phenotyping, and likelihood-ratio gene prioritization.

Biallelic variants in TUBGCP6 result in microcephaly and chorioretinopathy 1: Report of four cases and a literature review.

Autosomal recessive microcephaly and chorioretinopathy-1 (MCCRP1) is a rare Mendelian disorder resulting from biallelic loss of function variants in Tubulin-Gamma Complex Associated Protein 6 (TUBGCP6, MIM#610053). Clinical features of this disorder include microcephaly, cognitive impairment, dysmorphic features, and variable ophthalmological anomalies including chorioretinopathy. Microcephaly can be recognized prenatally and visual impairment becomes evident during the first year of life. The clinical presentation resembles the findings in some acquired conditions such as congenital toxoplasmosis and cytomegalovirus infections; thus, it is important to recognize and diagnose this syndrome in view of its impact on patient health management and familial reproductive plans. To date, only seven molecularly confirmed patients from five unrelated families have been reported. We report an additional four unrelated patients with TUBGCP6 variants including one prenatal diagnosis and review the clinical phenotypes and genotypes of all the known cases. This report expands the molecular and phenotypic spectrum of TUBGCP6 and includes additional prenatal findings associated with MCCRP1.

Association between complete right bundle branch block and atrial fibrillation development.

BACKGROUND: Complete right bundle branch block (CRBBB) is an important predictor of atrial fibrillation (AF) recurrence after pulmonary vein isolation. However, the association between CRBBB and AF development remains unclear. METHODS: We performed a retrospective study of 2639 patients (male, n = 1549; female, n = 1090; mean age, 58 ± 13 years). CRBBB was defined as a late R (R') wave in lead V1 or V2 with a slurred S wave in lead I and/or lead V6 with a prolonged QRS duration (≥120 ms). RESULTS: Among the 2639 patients, CRBBB was detected in 40 patients (1.5%), and the prevalence of AF was 7.4% (196/2639). The proportion of patients with AF and CRBBB was higher than the proportion of patients with AF without CRBBB (22.5% vs. 7.2%; p = 0.001). In the forward multivariate logistic analysis, CRBBB (odds ratio [OR], 3.329; 95% confidence interval [CI], 1.350-8.211; p = 0.009), complete left bundle branch block (OR, 2.209; 95% CI, 1.238-3.940; p = 0.007), age (OR, 1.020; 95% CI, 1.005-1.035; p = 0.009), valvular heart disease (OR, 2.332; 95% CI, 1.531-3.552; p < 0.001), left atrial diameter (OR, 1.133; 95% CI, 1.104-1.163; p < 0.001), left ventricular ejection fraction (OR, 1.023; 95% CI, 1.006-1.041; p = 0.007), and class I or III anti-arrhythmic drug use (OR, 10.534; 95% CI, 7.090-15.651; p < 0.001) were associated with AF. CONCLUSION: Complete right bundle branch block was significantly associated with AF development in hospitalized patients with cardiovascular diseases.

Effect of catheter ablation on clinical outcomes in patients with atrial fibrillation and significant functional mitral regurgitation.

BACKGROUND: In patients with atrial fibrillation (AF) and functional mitral regurgitation (MR), catheter ablation reduces the severity of MR and improves cardiac remodeling. However, its effects on prognosis are uncertain. METHODS: This retrospective study included 151 consecutive patients with AF and functional MR, 82 (54.3%) of whom were treated by catheter ablation (Ablation group) and 69 (45.7%) with drug therapy without ablation (Non-ablation group). Forty-three pairs of these patients were propensity matched on the basis of age, CHA2DS2-VASc scores, and left ventricular ejection fraction. The primary outcome evaluated was severity of MR, cardiac remodeling and the combined incidence of subsequent heart failure-related hospitalization and strokes/transient ischemic attacks. RESULTS: Patients in the Ablation group showed a significant decrease in the severity of MR (p < 0.001), a significant decrease in the left atrial diameter (p = 0.010), and significant improvement in the left ventricular ejection fraction (p = 0.015). However, patients in the Non-ablation group showed only a significant decrease in the severity of MR (p = 0.004). The annual incidence of the studied events was 4.9% in the Ablation group and 16.7% in the Non-ablation group, the incidence being significantly lower in the ablation than Non-ablation group (p = 0.026) according to Kaplan-Meier curve analyses. According to multivariate Cox regression analysis, catheter ablation therapy (hazard ratio [HR] 0.27, 95% confidence interval [CI] 0.09-0.84; p = 0.024) and heart failure at baseline (HR 3.84, 95% CI 1.07-13.74; p = 0.038) were independent predictors of the incidence of the studied events. CONCLUSIONS: Among patients with AF and functional MR, catheter ablation was associated with a significantly lower combined risk of heart failure-related hospitalization and stroke than in a matched cohort of patients receiving drug therapy alone.

A unified framework for association and prediction from vertex-wise grey-matter structure.

The recent availability of large-scale neuroimaging cohorts facilitates deeper characterisation of the relationship between phenotypic and brain architecture variation in humans. Here, we investigate the association (previously coined morphometricity) of a phenotype with all 652,283 vertex-wise measures of cortical and subcortical morphology in a large data set from the UK Biobank (UKB; N = 9,497 for discovery, N = 4,323 for replication) and the Human Connectome Project (N = 1,110). We used a linear mixed model with the brain measures of individuals fitted as random effects with covariance relationships estimated from the imaging data. We tested 167 behavioural, cognitive, psychiatric or lifestyle phenotypes and found significant morphometricity for 58 phenotypes (spanning substance use, blood assay results, education or income level, diet, depression, and cognition domains), 23 of which replicated in the UKB replication set or the HCP. We then extended the model for a bivariate analysis to estimate grey-matter correlation between phenotypes, which revealed that body size (i.e., height, weight, BMI, waist and hip circumference, body fat percentage) could account for a substantial proportion of the morphometricity (confirmed using a conditional analysis), providing possible insight into previous MRI case-control results for psychiatric disorders where case status is associated with body mass index. Our LMM framework also allowed to predict some of the associated phenotypes from the vertex-wise measures, in two independent samples. Finally, we demonstrated additional new applications of our approach (a) region of interest (ROI) analysis that retain the vertex-wise complexity; (b) comparison of the information retained by different MRI processings.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Epistasis analysis for quantitative traits by functional regression model.

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study.

An association study revealed substantial effects of dominance, epistasis and substance dependence co-morbidity on alcohol dependence symptom count.

Alcohol dependence is a complex disease involving polygenes, environment and their interactions. Inadequate consideration of these interactions may have hampered the progress on genome-wide association studies of alcohol dependence. By using the dataset of the Study of Addiction: Genetics and Environment with 3838 subjects, we conducted a genome-wide association studies of alcohol dependence symptom count (ADSC) with a full genetic model considering additive, dominance, epistasis and their interactions with ethnicity, as well as conditions of co-morbid substance dependence. Twenty quantitative trait single nucleotide polymorphisms (QTSs) showed highly significant associations with ADSC, including four previously reported genes (ADH1C, PKNOX2, CPE and KCNB2) and the reported intergenic rs1363605, supporting the overall validity of the analysis. Two QTSs within or near ADH1C showed very strong association in a dominance inheritance mode and increased the phenotype value of ADSC when the effect of co-morbid opiate or marijuana dependence was controlled. Highly significant association was also identified in variants within four novel genes (RGS6, FMN1, NRM and BPTF), two non-coding RNA and two epistasis loci. QTS rs7616413, located near PTPRG encoding a protein tyrosine phosphatase receptor, interacted with rs10090742 within ANGPT1 encoding a protein tyrosine phosphatase in an additive × additive or dominance × additive manner. The detected QTSs contributed to about 20 percent of total heritability, in which dominance and epistasis effects accounted for over 50 percent. These results demonstrated that perturbations arising from gene-gene interaction and conditions of co-morbidity substantially influence the genetic architecture of complex trait.

TNF/TNFR1 pathway and endoplasmic reticulum stress are involved in ofloxacin-induced apoptosis of juvenile canine chondrocytes.

BACKGROUND AND PURPOSE: Quinolones cause obvious cartilaginous lesions in juvenile animals by chondrocyte apoptosis, which results in the restriction of their use in pediatric and adolescent patients. Studies showed that chondrocytes can be induced to produce TNFα, and the cisternae of the endoplasmic reticulum in quinolone-treated chondrocytes become dilated. We investigated whether TNF/TNFR1 pathway and endoplasmic reticulum stress (ERs) are involved in ofloxacin (a typical quinolone)-induced apoptosis of juvenile canine chondrocytes. EXPERIMENTAL APPROACH: Canine juvenile chondrocytes were treated with ofloxacin. Cell survival and apoptosis rates were determined with MTT method and flow cytometry, respectively. The gene expression levels of the related signaling molecules (TNFα, TNFR1, TRADD, FADD and caspase-8) in death receptor pathways and main apoptosis-related molecules (calpain, caspase-12, GADD153 and GRP78) in ERs were measured by qRT-PCR. The gene expression of TNFR1 was suppressed with its siRNA. The protein levels of TNFα, TNFR1 and caspase-12 were assayed using Western blotting. KEY RESULTS: The survival rates decreased while apoptosis rates increased after the chondrocytes were treated with ofloxacin. The mRNA levels of the measured apoptosis-related molecules in death receptor pathways and ERs, and the protein levels of TNFα, TNFR1 and caspase-12 increased after the chondrocytes were exposed to ofloxacin. The downregulated mRNA expressions of TNFR1, Caspase-8 and TRADD, and the decreased apoptosis rates of the ofloxacin-treated chondrocytes occurred after TNFR1-siRNA interference. CONCLUSIONS AND IMPLICATIONS: Ofloxacin-induced chondrocyte apoptosis in a time- and concentration-dependent fashion. TNF/TNFR1 pathway and ERs are involved in ofloxacin-induced apoptosis of juvenile canine chondrocytes in the early stage.

Oral nifedipine may be a preferential option for treating acute severe hypertension during pregnancy: a meta-analysis.

AIM: To compare oral nifedipine and intravenous labetalol in the treatment of acute severe hypertension in pregnancy (SHP). METHODS: The primary outcomes were the required time to achieve target blood pressure (RTATBP), systolic blood pressure (SBP) and diastolic BP (DBP) after treatment, secondary outcomes were the number of doses (NoD) and adverse events (AEs). RESULTS: There was no difference between oral nifedipine and intravenous labetalol in SBP, DBP, and AE. However, oral nifedipine provided less RTATBP and NoD. CONCLUSION: Oral nifedipine was associated with less RTATBP and NoD and otherwise did not differ from intravenous labetalol.

Novel risk prediction models for deep vein thrombosis after thoracotomy and thoracoscopic lung cancer resections, involving coagulation and immune function.

The main focus of this study was to compare the predictive value of coagulation, fibrinolysis, thromboelastography, stress response, and immune function in predicting the incidence of deep venous thrombosis (DVT) in lung cancer (LC) patients undergoing thoracoscopic LC resection vs thoracotomy LC resection. To do that, a prospective, single-center, case-control study involving 460 LC patients was conducted. The risk indicators affecting patients with DVT after LC resection in the testing cohort were determined using logistic regression and receiver operator characteristic (ROC) analyses. One validation cohort was used to assess the risk prediction models. DVT incidence was higher in the thoracoscopic group (18.7%) than in the thoracotomy group (11.2%) in the testing cohort (χ 2 = 4.116, P = 0.042). The final model to predict the incidence of DVT after thoracoscopic LC excision (1 day after surgery) was as follows: Logit(P) = 9.378 - 0.061(R-value) - 0.109(K value) + 0.374(α angle) + 0.403(MA) + 0.298(FIB) + 0.406(D-D) + 0.190(MDA) - 0.097(CD4+/CD8+). For thoracotomy LC resection, the final model (3 days after operation) was: Logit(P) = -2.463 - 0.026(R-value) - 0.143(K value) + 0.402(α angle) + 0.198(D-D) + 0.237(MDA) + 0.409(SOD). In the validation cohort, this risk prediction model continued to demonstrate good predictive performance. As a result, the predictive accuracy of postoperative DVT in patients who underwent thoracoscopic LC resection and thoracotomy LC resection was improved by risk prediction models.

Efficacy of catheter ablation for atrial fibrillation in patients with significant functional mitral regurgitation.

BACKGROUND: Catheter ablation has been established to be an effective therapy for paroxysmal atrial fibrillation (AF) and is recommended as the treatment of choice for many patients, including those with clinically significant functional mitral regurgitation (MR). However, there is little information available about the clinical efficacy of catheter ablation for paroxysmal AF in patients with significant functional MR. METHODS: We performed a retrospective study of 247 patients with paroxysmal AF who underwent AF ablation. The study included 28 (11.3%) patients with significant functional MR and 219 (88.7%) without significant functional MR. AF recurrence was defined as the occurrence of confirmed atrial tachyarrhythmia lasting >30 seconds beyond 3 months after catheter ablation. RESULTS: During a mean follow-up of 20.1 ± 7.4 months (range, 3-36 months), 45 (18.2%) patients developed recurrence of AF. The recurrence rate of AF was higher in patients with significant functional MR than in those without significant functional MR (42.9% vs 15.1%; P < .001). Univariable Cox proportional hazards regression analysis showed that significant functional MR (hazard ratio [HR], 3.46; 95% confidence interval [CI], 1.78-6.72; P < .001), age (HR, 1.04; 95% CI, 1.01-1.08; P = .009), the CHA2DS2-VASc score (HR, 1.28; 95% CI, 1.05-1.56; P = .017), and heart failure (HR, 4.71; 95% CI, 1.85-11.96; P = .001) were associated with the risk of recurrence. Multivariable analysis showed that significant functional MR (HR, 2.48; 95% CI, 1.21-5.05; P = .013), age (HR, 1.04; 95% CI, 1.00-1.07; P = .031), and heart failure (HR, 3.39; 95% CI, 1.27-9.03; P = .015) were independent predictors of AF recurrence. CONCLUSION: Patients with significant functional MR have an increased risk of AF recurrence after catheter ablation.

Analysis of risk factors and short-term prognostic factors of arrhythmia in patients infected with mild/moderate SARS-CoV-2 Omicron variant.

Background: Complications, including arrhythmia, following severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection continue to be of concern. Omicron is the mainstream SARS-CoV-2 mutant circulating in mainland China. At present, there are few epidemiological studies concerning the relationship between arrhythmia and Omicron variant infection in mainland China. Objectives: To investigate the risk factors of arrhythmia in patients infected with the SARS-CoV-2 Omicron variant and the factors influencing prognosis. Methods: Data from 192 Omicron infected patients with symptoms of arrhythmia (AH group) and 100 Omicron infected patients without arrhythmia (Control group) were collected. Patients in the AH group were divided into the good and poor prognosis groups, according to the follow-up results 4-6 weeks after infection. The general and clinical data between the AH and Control groups, and between the good and poor prognosis groups were compared. The variables with differences between the groups were included in the multivariate logistic regression analysis, and the quantitative variables were analyzed by receiver operating characteristic curve to obtain their cut-off values. Results: Compared with the control group, the body mass index (BMI), proportion of patients with a history of arrhythmia, proportion of antibiotics taken, heart rate, moderate disease severity, white blood cell (WBC) count, and the aspartate aminotransferase, creatine kinase (CK), CK isoenzyme (CK-MB), myoglobin (Mb), high-sensitive troponin I (hs-cTnI), lymphocyte ratio and high sensitivity C-reactive protein (hs-CRP) levels in the AH group were significantly higher (p < 0.05). In addition, obesity (BMI ≥24 kg/m2), fast heart rate (≥100 times/min), moderate disease severity, and WBC, CK-MB and hs-cTnI levels were independent risk factors of arrhythmia for patients with Omicron infection (p < 0.05), and hs-CRP was a protective factor (p < 0.05). Compared with the good prognosis group, the age, proportion of patients with a history of arrhythmia, heart rate, proportion of moderate disease severity, and hs-CRP, CK, Mb and hs-cTnI levels were significantly higher in the poor prognosis group, while the proportion of vaccination was lower in the poor prognosis group (p < 0.05). Advanced age (≥65 years old), proportion of history of arrhythmia, moderate disease severity, vaccination, and hs-CRP, Mb and cTnI levels were independent factors for poor prognosis of patients with arrhythmia (p < 0.05). Conclusion: The factors that affect arrhythmia and the prognosis of patients infected with Omicron include obesity, high heart rate, severity of the disease, age. history of arrhythmia, WBC, hs-CRP, and myocardial injury indexes, which could be used to evaluate and prevent arrhythmia complications in patients in the future.

miR-141-3p Reduces Cell Migration and Proliferation in an In Vitro Modelof Atherosclerosis by Targeting Wnt5a.

BACKGROUND: Atherosclerosis (AS) is a type of chronic vascular disease that is also a leading cause of numerous cardiovascular diseases in humans. The biomolecules responsible for the roles of microRNA (miR)-141-3p during AS development are less understood. METHODS: The relation between Wnt5a and miR-141-3p was predicted using bioinformatics software TargetScan 7.1, and confirmed via dual luciferase reporter assay. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunoblotting were conducted for examining miR-141-3p and Wingless and Int-1 (Wnt)5a expression levels. Additionally, transwell migration and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays were conducted for analyzing cell migration and proliferation, respectively. RESULTS: miR-141-3p was decreased in oxidized low-density lipoprotein (ox-LDL)-treated human vascular smooth muscle cells (VSMCs). Pretreatment with miR-141-3p mimic inhibited cell migration and proliferation in ox-LDL-induced VSMCs. Wnt5a was verified to act as the target of miR-141-3p in VSMCs. pcDNA3-Wnt5a partially reversed the effects of miR-141-3p mimic in ox-LDL-stimulated VSMCs. CONCLUSION: miR-141-3p mimic decreased the damage in an AS model by targeting Wnt5a, thereby presenting a novel potential therapeutic target for treating AS.

Responses of soil mineral-associated and particulate organic carbon to carbon input: A meta-analysis.

A minor change of soil organic carbon (SOC) greatly influences atmospheric carbon dioxide concentration and climate change. Exogenous carbon (C) input into soils can induce SOC decomposition or sequestration. The response of SOC to C input can be better understood when SOC is separated into mineral-associated (MAOC) and particulate (POC) organic carbon. The objective of this study is to explore whether exogenous C input promote MAOC and POC increase or decrease and the controlling factors. We gained 1181 observations from 17 studies for this meta-analysis. The effect sizes of exogenous C input on MAOC and POC content, and MAOC decomposition were calculated. The key factors influencing the effect sizes were explored through subgroup analysis. Potential publication bias was explored by using funnel plots, trim and fill method, and Egger's test. Exogenous C input significantly increased MAOC and POC content, although promoted MAOC decomposition. The effect sizes were larger for MAOC content than for POC content irrespective of soil and substrate properties and experiment methods. The effects of C input on MAOC and POC content were more pronounced in forest soils, and depended on the C and nitrogen (N) content in soil and substrates as well as experiment methods. The effect size of C input on MAOC decomposition were larger with substrate input of below 200 g C kg-1 in specific soils. The sensitivity analysis carried out by removing one observation indicated our results were robust. In conclusion, exogenous C input increases MAOC and POC content although stimulate MAOC decomposition, and the effect sizes were influenced mainly by ecosystem type, carbon and nitrogen content of substrates and soils, and fractionation methods. The findings indicate the importance of C and N content in substrates and soils in controlling the response of SOC rather than the ratio of C to N.

Genetic control of RNA splicing and its distinct role in complex trait variation.

Most genetic variants identified from genome-wide association studies (GWAS) in humans are noncoding, indicating their role in gene regulation. Previous studies have shown considerable links of GWAS signals to expression quantitative trait loci (eQTLs) but the links to other genetic regulatory mechanisms, such as splicing QTLs (sQTLs), are underexplored. Here, we introduce an sQTL mapping method, testing for heterogeneity between isoform-eQTL effects (THISTLE), with improved power over competing methods. Applying THISTLE together with a complementary sQTL mapping strategy to brain transcriptomic (n = 2,865) and genotype data, we identified 12,794 genes with cis-sQTLs at P < 5 × 10-8, approximately 61% of which were distinct from eQTLs. Integrating the sQTL data into GWAS for 12 brain-related complex traits (including diseases), we identified 244 genes associated with the traits through cis-sQTLs, approximately 61% of which could not be discovered using the corresponding eQTL data. Our study demonstrates the distinct role of most sQTLs in the genetic regulation of transcription and complex trait variation.

Parsimonious model for mass-univariate vertexwise analysis.

Purpose: Covariance between gray-matter measurements can reflect structural or functional brain networks though it has also been shown to be influenced by confounding factors (e.g., age, head size, and scanner), which could lead to lower mapping precision (increased size of associated clusters) and create distal false positives associations in mass-univariate vertexwise analyses. Approach: We evaluated this concern by performing state-of-the-art mass-univariate analyses (general linear model, GLM) on traits simulated from real vertex-wise gray matter data (including cortical and subcortical thickness and surface area). We contrasted the results with those from linear mixed models (LMMs), which have been shown to overcome similar issues in omics association studies. Results: We showed that when performed on a large sample ( N = 8662 , UK Biobank), GLMs yielded greatly inflated false positive rate (cluster false discovery rate > 0.6 ). We showed that LMMs resulted in more parsimonious results: smaller clusters and reduced false positive rate but at a cost of increased computation. Next, we performed mass-univariate association analyses on five real UKB traits (age, sex, BMI, fluid intelligence, and smoking status) and LMM yielded fewer and more localized associations. We identified 19 significant clusters displaying small associations with age, sex, and BMI, which suggest a complex architecture of at least dozens of associated areas with those phenotypes. Conclusions: The published literature could contain a large proportion of redundant (possibly confounded) associations that are largely prevented using LMMs. The parsimony of LMMs results from controlling for the joint effect of all vertices, which prevents local and distal redundant associations from reaching significance.

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.

BACKGROUND: People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. RESULTS: We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. CONCLUSIONS: We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.