PAX7 target genes are globally repressed in facioscapulohumeral muscular dystrophy skeletal muscle

Facioscapulohumeral muscular dystrophy (FSHD) is a prevalent, incurable myopathy, linked to hypomethylation of D4Z4 repeats on chromosome 4q causing expression of the DUX4 transcription factor. However, DUX4 is difficult to detect in FSHD muscle biopsies and it is debatable how robust changes in DUX4 target gene expression are as an FSHD biomarker. PAX7 is a master regulator of myogenesis that rescues DUX4-mediated apoptosis. Here, we show that suppression of PAX7 target genes is a hallmark of FSHD, and that it is as major a signature of FSHD muscle as DUX4 target gene expression. This is shown using meta-analysis of over six FSHD muscle biopsy gene expression studies, and validated by RNA-sequencing on FSHD patient-derived myoblasts. DUX4 also inhibits PAX7 from activating its transcriptional target genes and vice versa. Furthermore, PAX7 target gene repression can explain oxidative stress sensitivity and epigenetic changes in FSHD. Thus, PAX7 target gene repression is a hallmark of FSHD that should be considered in the investigation of FSHD pathology and therapy

Dynamic transcriptomic analysis reveals suppression of PGC1α/ERRα drives perturbed myogenesis in facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is a prevalent, incurable myopathy, linked to epigenetic de-repression of D4Z4 repeats on chromosome 4q, leading to ectopic DUX4 expression. FSHD patient myoblasts have defective myogenic differentiation, forming smaller myotubes with reduced myosin content. However, molecular mechanisms driving such disrupted myogenesis in FSHD are poorly understood. We performed high-throughput morphological analysis describing FSHD and control myogenesis, revealing altered myogenic differentiation results in hypotrophic myotubes. Employing polynomial models and an empirical Bayes approach, we established eight critical time-points during which human healthy and FSHD myogenesis differ. RNA-sequencing at these eight nodal time-points in triplicate, provided temporal depth for a multivariate regression analysis, allowing assessment of interaction between progression of differentiation and FSHD disease status. Importantly, the unique size and structure of our data permitted identification of many novel FSHD pathomechanisms undetectable by previous approaches. Selected for further analysis here, were pathways that control mitochondria: of interest considering known alterations in mitochondrial structure and function in FSHD muscle, and sensitivity of FSHD cells to oxidative stress. Notably, we identified suppression of mitochondrial biogenesis, in particular via PGC1α, the co-factor and activator of ERRα. PGC1α knock-down caused hypotrophic myotubes to form from healthy myoblasts. Known ERRα agonists and safe food supplements Biochanin A, Genistein or Daidzein, each rescued the hypotrophic FSHD myotube phenotype. Together our work describes transcriptomic changes in high resolution that occur during myogenesis in FSHD ex-vivo, identifying suppression of the PGC1α-ERRα axis leading to perturbed myogenic differentiation, which can effectively be rescued by readily-available food supplements

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

15. Sensitivity in visualizing vegetations in cardiac lead-induced endocarditis: A comparative study between transesophageal vs. transthoracic echocardiography

Despite advancement in sterile cardiac device implantation techniques, wound infections and/or bacteremia remain a significant problem. The presence of a vegetation in lead-induced endocarditis (LIE) is a critical factor that determines the management. Transthoracic (TTE) and Transesophageal (TEE) Echocardiography are two different cardiac modalities that are used for the detection of lead vegetation. However, it is not yet clear which of the two has the highest diagnostic accuracy. We aim to identify which of the two has the highest sensitivity. In addition, we aim to correlate the existence of a vegetation with blood and wound culture results. We conducted a chart review in 113 patients whom underwent lead extraction at Prince Sultan Cardiac Center in Saudi Arabia during the period of Jan, 2002 to Jul, 2015. Six patients underwent lead extraction twice, increasing the number to be a total of 119 cases. Out of the study cohort, we include 38 patients who had both TTE and TEE done prior to lead extraction. Data regarding TTE, TEE, as well as blood and wound cultures were collected from echocardiography and microbiology lab reports using a well-structured case report form.Of the study population, 21 patients (55.3%) had lead vegetations visualized either by TTE or TEE. Nineteen patients had vegetations detected by TEE, compared to 6 patients only when TTE was used. The sensitivity of TEE and TTE were 90.5% (CI: 69.6–98.8%) and 28.5% (95% CI: 11.3–52.1%), respectively. Blood and wound culture results showed that in the presence of a vegetation, blood cultures were positive in 55% of the cases (P=0.036) while only 44.4% of those with vegetations had a positive wound culture (P=0.347). TEE has higher sensitivity in detecting vegetations compared to TTE in LIE. The presence of a vegetation is more likely to be associated with a positive blood culture than a positive wound culture. Further studies ought to measure the accuracy of different modalities for capturing a vegetative lead. That is, measuring the additive value of blood and wound cultures to the overall cardiac imaging sensitivity, and to calculate the sensitivity of the combined techniques

10. Effect of pacemaker/defibrillator lead extraction on pulmonary artery systolic pressure

As the number of cardiac device implantations are on a rise, there is a parallel increase in their long-term complications including device-related infection that will require lead extraction. As the detachment of fibrosed debris reaching the pulmonary trunk can occur during the extraction, the risk of developing new-onset Pulmonary Hypertension (P. HTN) increases with every extraction. Yet, there is paucity of evidence to support such claim. Given the clinical significance of such findings, we sought to determine the risk. A chart review of 113 patients whom underwent lead extraction at Prince Sultan Cardiac Center in Saudi Arabia during the period of Jan, 2002 to Jul, 2015 was carried out. Six patients had lead extraction twice, making the total number of extractions to be 119. Of this study cohort, only 45 cases had Pulmonary Artery Systolic Pressure (PASP) measurement via Transthoracic Echocardiography (TTE) prior to and after device extraction. PASP measurements were obtained as reported whether a single measurement or a range between two readings, and an average was calculated in case of two readings. A difference of 10 mmHg or more in the PASP, whether progression or improvement, was considered clinically significant.Median follow up of TTE after lead and device extraction was 5 months. Out of 45 patients, 31 (68.9%) were males and 14 (31.1%) were females. Average age was 46.5 (SD = 17) years. Eleven patients (24.4%) experienced a significant increase of PASP after lead extraction (10 had normal pressure readings before extraction, and only one had progression to a more severe form of the disease), 9 patients (20.0%) showed improvement, and the remaining (55.6%) did not show any significant change in PASP. Average implantation-to-extraction duration of the leads was higher among those who had no pressure difference (50.6 vs. 23.3 months). When looking through potential predictors that may increase the likelihood of developing P. HTN, there was no association with a pre-existing lead-attached vegetation (2 patients only), nor the type of lead (6 high-voltage vs. 5 pacing leads across the tricuspid valve). In patients who developed P. HTN, 8 (72.7%) had their devices extracted as a result of a complicated infection (wound infections and/or infective endocarditis), as opposed to 3 (27.3%) whom underwent device extraction for other indications. Our simple descriptive study showed that the risk of developing P. HTN following lead and device extraction is negligible. However, our findings should be interpreted in the light of the limitations such as a small sample size and lack of comparable control group. Paucity of data and evidence on the long-term complications subsequent to device and lead extractions will be a subject of further exploration given the potential connection to patient outcomes and management

9. Incidence of tricuspid valve regurgitation following pacemaker/defibrillator lead extraction

Despite advanced sterile techniques in cardiac device implantations, long-term complications such as wound infections and/or lead-induced endocarditis can develop mandating lead and device extraction. It has been suggested that lead extraction carries a risk of new-onset Tricuspid Regurgitation (TR), or a deterioration of a formerly known regurgitant valve. Yet, there is no enough scientific evidence to our knowledge to back this claim. In this study we aim to explore the risk of TR following lead extraction.We conducted a retrospective chart review in 113 patients whom underwent lead extraction at Prince Sultan Cardiac Center in Saudi Arabia during the period of Jan, 2002 to Jul, 2015. Six patients underwent lead extraction twice, making the total number of extractions to be 119. Of this study cohort, we include 52 cases who had Tricuspid valve function evaluation via Transthoracic Echocardiography (TTE) prior to and after device and lead extraction. TR severity was assessed using a grading system as the following; normal, mild, mild-to-moderate, moderate-to-severe, and severe. Worsening or improvement by more than 1 grade was considered clinically significant. TR following lead extraction was examined over a median of 5 months. Of the 52 cases included in this study, 37 (71.2%) were males and 15 (28.8%) were females, with a mean age of 46 (SD = 18) years. Eleven patients (21.2%) experienced worsening of TR (3 had normal functioning valves before extraction, and 8 were known to have TR prior to extraction), 2 (3.8%) had improvement, and the majority (75.0%) did not experience any significant changes. Compared with those who had no change, average lead duration was higher in the worsening TR group (67.2 vs. 27.9 months). A lead-attached vegetation was detected in 4 out of the 11 patients with TR. Lead type (High-voltage vs. Pacing) was not predictive of TR, 5 (45.5%) of the patients in the worsening group had high-voltage leads, while the remaining (54.5%) had pacing leads across the valve.Our study being a simple descriptive study could not find overwhelming evidence to support the claim that there is an elevated risk of new onset TR or deterioration of a regurgitant valve following pacemaker/defibrillator lead extraction. However, our study being a simple observational study with a considerably small sample size may influence the findings. Lack of appropriate control group in this study is a limitation in appraising the hypothesis. As there is scarcity of data in this important area of cardiac research, our findings should prompt motivation for larger and well controlled cohort studies

The chromatin remodeling factor CHD7 controls cerebellar development by regulating reelin expression

10.1172/JCI83408Journal of Clinical Investigation1273874-88

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies

One goal of human genetics is to understand the genetic basis of disease, a challenge for diseases of complex inheritance because risk alleles are few relative to the vast set of benign variants. Risk variants are often sought by association studies in which allele frequencies in case subjects are contrasted with those from population-based samples used as control subjects. In an ideal world we would know population-level allele frequencies, releasing researchers to focus on case subjects. We argue this ideal is possible, at least theoretically, and we outline a path to achieving it in reality. If such a resource were to exist, it would yield ample savings and would facilitate the effective use of data repositories by removing administrative and technical barriers. We call this concept the Universal Control Repository Network (UNICORN), a means to perform association analyses without necessitating direct access to individual-level control data. Our approach to UNICORN uses existing genetic resources and various statistical tools to analyze these data, including hierarchical clustering with spectral analysis of ancestry; and empirical Bayesian analysis along with Gaussian spatial processes to estimate ancestry-specific allele frequencies. We demonstrate our approach using tens of thousands of control subjects from studies of Crohn disease, showing how it controls false positives, provides power similar to that achieved when all control data are directly accessible, and enhances power when control data are limiting or even imperfectly matched ancestrally. These results highlight how UNICORN can enable reliable, powerful, and convenient genetic association analyses without access to the individual-level data.One goal of human genetics is to understand the genetic basis of disease, a challenge for diseases of complex inheritance because risk alleles are few relative to the vast set of benign variants. Risk variants are often sought by association studies in which allele frequencies in case subjects are contrasted with those from population-based samples used as control subjects. In an ideal world we would know population-level allele frequencies, releasing researchers to focus on case subjects. We argue this ideal is possible, at least theoretically, and we outline a path to achieving it in reality. If such a resource were to exist, it would yield ample savings and would facilitate the effective use of data repositories by removing administrative and technical barriers. We call this concept the Universal Control Repository Network (UNICORN), a means to perform association analyses without necessitating direct access to individual-level control data. Our approach to UNICORN uses existing genetic resources and various statistical tools to analyze these data, including hierarchical clustering with spectral analysis of ancestry; and empirical Bayesian analysis along with Gaussian spatial processes to estimate ancestry-specific allele frequencies. We demonstrate our approach using tens of thousands of control subjects from studies of Crohn disease, showing how it controls false positives, provides power similar to that achieved when all control data are directly accessible, and enhances power when control data are limiting or even imperfectly matched ancestrally. These results highlight how UNICORN can enable reliable, powerful, and convenient genetic association analyses without access to the individual-level data