Knowledge, attitudes, practices and intention to get vaccinated against COVID-19: results from a cross-sectional survey in three peri-urban communities in South Africa.

Introduction: South Africa has the largest number of confirmed cases of COVID-19 in Africa. Data to inform public health strategies to mitigate the spread of new variants and severity of disease is needed, including information on knowledge, attitudes and practices (KAP) regarding COVID-19, factors associated with intention to get vaccinated, and viewpoints on reliable sources of data. Methods: we investigated these topics as part of the COVID-19 healthcare utilization and seroprevalence (HUTS) cross-sectional survey in three communities in South Africa: Mitchell´s Plain (Western Cape Province), Pietermaritzburg (KwaZulu-Natal Province) and Klerksdorp (North West Province) during and after the second wave of COVID-19 prior to vaccine availability. Results: primary caregivers from 5799 households participated in the study, 41.1% from Pietermaritzburg, 34.2% from Klerksdorp and 24.7% from Mitchells Plain. Two-thirds and 94.7% of respondents had correct knowledge on the cause and spread of COVID-19, respectively. Knowledge measures were significantly associated with age less than 65 years, the highest level of education and site (Mitchells Plain). Desired preventive behaviors were associated with higher socio-economic status. While 64.7% of people intended to get vaccinated, those over 64 years of age were more likely to intend to vaccinate (aOR: 1.25, 95% CI: 1.06-1.47). Vaccine intention related to protection of self (58.4%) and family (40.0%). The most trusted source of COVID-19 information was television (59.3%) followed by radio (20.0%). Conclusion: these data can be used to design targeted public health campaigns for the current COVID-19 and future epidemics, ensuring that socio-economic constraints and preference for trusted information are considered.

Healthcare utilization during the first two waves of the COVID-19 epidemic in South Africa: A cross-sectional household survey.

Healthcare utilization surveys contextualize facility-based surveillance data for burden estimates. We describe healthcare utilization in the catchment areas for sentinel site healthcare facilities during the first year of the COVID-19 pandemic. We conducted a cross-sectional healthcare utilization survey in households in three communities from three provinces (KwaZulu-Natal, Western Cape and North West). Field workers administered structured questionnaires electronically with the household members reporting influenza-like illness (ILI) in the past 30 days or severe respiratory illness (SRI) since March 2020. Multivariable logistic regression was used to identify factors associated with healthcare utilization among individuals that reported illness. From November 2020 through April 2021, we enrolled 5804 households and 23,003 individuals. Any respiratory illness was reported by 1.6% of individuals; 0.7% reported ILI only, 0.8% reported SRI only, and 0.1% reported both ILI and SRI. Any form of medical care was sought by 40.8% (95% CI 32.9% - 49.6%) and 71.3% (95% CI 63.2% - 78.6%) of individuals with ILI and SRI, respectively. On multivariable analysis, respiratory illness was more likely to be medically attended for individuals at the Pietermaritzburg site (aOR 3.2, 95% CI 1.1-9.5, compared to Klerksdorp), that were underweight (aOR 11.5, 95% CI 1.5-90.2, compared to normal weight), with underlying illness (aOR 3.2, 95%CI 1.2-8.5), that experienced severe illness (aOR 4.8, 95% CI 1.6-14.3) and those with symptom duration of ≥10 days (aOR 7.9, 95% CI 2.1-30.2, compared to <5 days). Less than half of ILI episodes and only 71% of SRI episodes were medically attended during the first two COVID-19 waves in South Africa. Facility-based data may underestimate disease burden during the COVID-19 pandemic.

Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 After the Second Wave in South Africa in Human Immunodeficiency Virus-Infected and Uninfected Persons: A Cross-Sectional Household Survey.

BACKGROUND: Seroprevalence studies are important for quantifying the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in resource-constrained countries. METHODS: We conducted a cross-sectional household survey spanning the second pandemic wave (November 2020 to April 2021) in 3 communities. Blood was collected for SARS-CoV-2 antibody (2 enzyme-linked immunosorbent assays targeting spike and nucleocapsid) and human immunodeficiency virus (HIV) testing. An individual was considered seropositive if testing positive on ≥1 assay. Factors associated with infection, and the age-standardized infection case detection rate, infection hospitalization rate, and infection fatality rate were calculated. RESULTS: Overall, 7959 participants were enrolled, with a median age of 34 years and an HIV prevalence of 22.7%. SARS-CoV-2 seroprevalence was 45.2% (95% confidence interval 43.7%-46.7%) and increased from 26.9% among individuals enrolled in December 2020 to 47.1% among those enrolled in April 2021. On multivariable analysis, seropositivity was associated with age, sex, race, being overweight/obese, having respiratory symptoms, and low socioeconomic status. Persons living with HIV with high viral load were less likely to be seropositive than HIV-uninfected individuals. The site-specific infection case detection rate, infection hospitalization rate, and infection fatality rate ranged across sites from 4.4% to 8.2%, 1.2% to 2.5%, and 0.3% to 0.6%, respectively. CONCLUSIONS: South Africa has experienced a large burden of SARS-CoV-2 infections, with <10% of infections diagnosed. Lower seroprevalence among persons living with HIV who are not virally suppressed, likely as a result of inadequate antibody production, highlights the need to prioritize this group for intervention.

ERα inhibits mesenchymal and amoeboidal movement of liver cancer cell via Gα12.

Hepatocellular carcinoma (HCC) is the second most common cancer worldwide, demonstrating aggressiveness and mortality more frequently in men than in women. Despite reports regarding the inhibitory ability of estrogen receptor alpha (ERα, ESR1) in certain cancer progression, targets and the basis of underlying gender disparity in HCC worsening remain elusive. Here, we report the ability of ERα to transcriptionally inhibit G protein subunit alpha 12 (Gα12) responsible for HCC worsening. First, using human samples and public database, the expression of ERα and Gα12 in HCC was examined. Then, quantitative real-time PCR, chromatin immunoprecipitation-assay, luciferase assay and immunoblottings of liver cancer cell lines confirmed the inhibitory ability of ERα on Gα12 and HCC progression. Gα12 promoted mesenchymal characteristics and amoeboidal movement, which was antagonized by ERα overexpression. Additionally, we found microRNA-141 and microRNA-200a as downstream targets of the Gα12 signaling axis for cancer malignancy regulation under the control of ERα. As for in-depth mechanism, PTP4A1 was found to be directly inhibited by microRNA-141 and microRNA-200a. Moreover, we found the inhibitory effect of ERα on amoeboidal movement by analyzing the morphology and blebbing of liver cancer cells and the active form of MLC levels. The identified targets and ESR1 levels are inversely correlated with human specimens, as well as with sex-biased survival rates of HCC patients. Collectively, ERα-dependent repression of Gα12 and consequent changes in the Gα12 signaling may explain the gender disparity in HCC, providing pharmacological clues for the control of metastatic HCC.

Combination of automated brain volumetry on MRI and quantitative tau deposition on THK-5351 PET to support diagnosis of Alzheimer's disease.

Imaging biomarkers support the diagnosis of Alzheimer's disease (AD). We aimed to determine whether combining automated brain volumetry on MRI and quantitative measurement of tau deposition on [18F] THK-5351 PET can aid discrimination of AD spectrum. From a prospective database in an IRB-approved multicenter study (NCT02656498), 113 subjects (32 healthy control, 55 mild cognitive impairment, and 26 Alzheimer disease) with baseline structural MRI and [18F] THK-5351 PET were included. Cortical volumes were quantified from FDA-approved software for automated volumetric MRI analysis (NeuroQuant). Standardized uptake value ratio (SUVR) was calculated from tau PET images for 6 composite FreeSurfer-derived regions-of-interests approximating in vivo Braak stage (Braak ROIs). On volumetric MRI analysis, stepwise logistic regression analyses identified the cingulate isthmus and inferior parietal lobule as significant regions in discriminating AD from HC and MCI. The combined model incorporating automated volumes of selected brain regions on MRI (cingulate isthmus, inferior parietal lobule, hippocampus) and SUVRs of Braak ROIs on [18F] THK-5351 PET showed higher performance than SUVRs of Braak ROIs on [18F] THK-5351 PET in discriminating AD from HC (0.98 vs 0.88, P = 0.033) but not in discriminating AD from MCI (0.85 vs 0.79, P = 0.178). The combined model showed comparable performance to automated volumes of selected brain regions on MRI in discriminating AD from HC (0.98 vs 0.94, P = 0.094) and MCI (0.85 vs 0.78; P = 0.065).

Intra-individual correlations between quantitative THK-5351 PET and MRI-derived cortical volume in Alzheimer's disease differ according to disease severity and amyloid positivity.

PURPOSE: To assess the in vivo whole-brain relationship between uptake of [18F]THK-5351 on PET and cortical atrophy on structural MRI according to the presence and severity of Alzheimer's disease (AD). MATERIALS AND METHODS: Sixty-five participants (21 normal controls, 32 mild cognitive impairment [MCI] subjects, and 12 AD patients) were enrolled from a prospective multicenter clinical trial (NCT02656498). Structural MRI and [18F]THK-5351 PET were performed within a 2-month interval. Cortical volume and standardized uptake value ratios (SUVR) were calculated from MRI and PET images, respectively, for 35 FreeSurfer-derived cortical regions. Pearson's correlation coefficients between SUVR and cortical volume were calculated for the same regions, and correlated regions were compared according to disease severity and ß-amyloid PET positivity. RESULTS: No significantly correlated regions were found in the normal controls. Negative correlations between SUVR and cortical volume were found in the MCI and AD groups, mainly in limbic locations in MCI and isocortical locations in AD. The AD group exhibited stronger correlations (r = -0.576-0.781) than the MCI group (r = 0.368-0.571). Hippocampal atrophy did not show any correlation with SUVR in the ß-amyloid PET-negative group, but negatively correlated with SUVR (r = -0.494, P = .012) in the ß-amyloid PET-positive group. CONCLUSIONS: Regional THK-5351 uptake correlated more strongly with cortical atrophy in AD compared with MCI, thereby demonstrating a close relationship between the neuro-pathologic process and cortical atrophy. Hippocampal atrophy was associated with both ß-amyloid and THK-5351 uptake, possibly reflecting an interaction between ß-amyloid and tau deposition in the neurodegeneration process.

Role of non-coding RNAs in liver disease progression to hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a tumor with poor prognosis and frequently aggressive. The development of HCC is associated with fibrosis and cirrhosis, which mainly results from nonalcoholic fatty liver disease, excessive alcohol consumption, and viral infections. Non-coding RNAs (ncRNAs) are RNAs transcribed from the genome, but are not translated into proteins. Recently, ncRNAs emerged as key contributors to tumor development and progression because of their abilities to regulate various targets and modulate cell proliferation, differentiation, apoptosis, and development. In this review, we summarize the frequently activated pathways in HCC and discuss the pathological implications of ncRNAs in the context of human liver disease progression, in particular HCC development and progression. This review aims to summarize the role of ncRNA dysregulation in the diseases and discuss the diagnostic and therapeutic potentials of ncRNAs.

Radiomics Analysis of Gadoxetic Acid-enhanced MRI for Staging Liver Fibrosis.

Purpose To develop and validate a radiomics-based model for staging liver fibrosis by using gadoxetic acid-enhanced hepatobiliary phase MRI. Materials and Methods In this retrospective study, 436 patients (mean age, 51 years; age range, 18-86 years; 319 men [mean age, 51 years; age range, 18-86 years]; 117 women [mean age, 50 years; age range, 18-79 years]) with pathologic analysis-proven liver fibrosis who underwent gadoxetic acid-enhanced MRI from June 2015 to December 2016 were randomized in a three-to-one ratio into development (n = 329) and test (n = 107) cohorts, respectively. In the development cohort, a model was developed to calculate radiomics fibrosis index (RFI) by using logistic regression with elastic net regularization to differentiate stage F3-F4 from stage F0-F2. Optimal RFI cutoffs to diagnose clinically significant fibrosis (stage F2-F4), advanced fibrosis (stage F3-F4), and cirrhosis (stage F4) were determined by receiver operating characteristic curve analysis. In the test cohort, the diagnostic performance of RFI was compared with that of normalized liver enhancement, aspartate transaminase-to-platelet ratio index (APRI), and fibrosis-4 index by using the Obuchowski index. Results In the test cohort, RFI (Obuchowski index, 0.86) significantly outperformed normalized liver enhancement (Obuchowski index, 0.77; P < .03), APRI (Obuchowski index, 0.60; P < .001), and fibrosis-4 index (Obuchowski index, 0.62; P < .001) for staging liver fibrosis. By using the cutoffs, RFI had sensitivities and specificities as follows: 81% (95% confidence interval: 71%, 89%) and 78% (95% confidence interval: 63%, 89%) for diagnosing stage F2-F4, respectively; 79% (95% confidence interval: 67%, 88%) and 82% (95% confidence interval: 69%, 91%), respectively, for diagnosing stage F3-F4; and 92% (95% confidence interval: 79%, 98%) and 75% (95% confidence interval: 62%, 83%), respectively, for diagnosing stage F4. Conclusion Radiomics analysis of gadoxetic acid-enhanced hepatobiliary phase images allows for accurate diagnosis of liver fibrosis. © RSNA, 2018 Online supplemental material is available for this article.

CT indices for the diagnosis of hepatic steatosis using non-enhanced CT images: development and validation of diagnostic cut-off values in a large cohort with pathological reference standard.

OBJECTIVES: To compare the performances of CT indices for diagnosing hepatic steatosis (HS) and to determine and validate the CT index cut-off values. METHODS: Three indices were measured on non-enhanced CT images of 4413 living liver donor candidates (2939 men, 1474 women; mean age, 31.4 years): hepatic attenuation (CTL), hepatic attenuation minus splenic attenuation (CTL-S), and hepatic attenuation divided by splenic attenuation (CTL/S). The performances of these CT indices in diagnosing HS, relative to pathologic diagnosis, were compared in the development cohort of 3312 subjects by receiver operating characteristic (ROC) analysis. The cut-off values for diagnosing HS > 33% in the development cohort were determined at 95% specificity and 95% sensitivity using bootstrap ROC analysis, and the diagnostic performance of these cut-off values was validated in the test cohort of 1101 subjects. RESULTS: CTL-S showed the highest performance for diagnosing HS ≥ 5% and HS > 33% (areas under the curve (AUCs) = 0.737 and 0.926, respectively), followed by CTL/S (AUCs = 0.732 and 0.925, respectively) and CTL (AUCs = 0.707 and 0.880, respectively). For CT scans using 120 kVp, the CTL-S cut-off values for highly specific (i.e., - 2.1) and highly sensitive (i.e., 7.6) diagnosis of HS > 33% resulted in a specificity of 96.4% with a sensitivity of 64.0% and a sensitivity of 97.3% with a specificity of 54.9%, respectively, in the test cohort. CONCLUSION: CT indices using liver and spleen attenuations have higher performance for diagnosing HS than indices using liver attenuation alone. The CTL-S cut-off values in this study may have utility for diagnosing HS in clinical practice and research. KEY POINTS: • CT indices based on both liver attenuation and spleen attenuation (CTL-Sand CTL/S) have higher diagnostic performance than CTLbased on liver attenuation alone in diagnosing HS using various CT techniques. • The CT index cut-off values determined in this study can be utilized for reliable diagnosis or to rule out subjects with moderate to severe HS in clinical practice and research, including the selection of living liver donors and the development of cohorts with HS or healthy controls.

Application of machine learning models in predicting length of stay among healthcare workers in underserved communities in South Africa.

BACKGROUND: Human resource planning in healthcare can employ machine learning to effectively predict length of stay of recruited health workers who are stationed in rural areas. While prior studies have identified a number of demographic factors related to general health practitioners' decision to stay in public health practice, recruitment agencies have no validated methods to predict how long these health workers will commit to their placement. We aim to use machine learning methods to predict health professional's length of practice in the rural public healthcare sector based on their demographic information. METHODS: Recruitment and retention data from Africa Health Placements was used to develop machine-learning models to predict health workers' length of practice. A cross-validation technique was used to validate the models, and to evaluate which model performs better, based on their respective aggregated error rates of prediction. Length of stay was categorized into four groups for classification (less than 1 year, less than 2 years, less than 3 years, and more than 3 years). R, a statistical computing language, was used to train three machine learning models and apply 10-fold cross validation techniques in order to attain evaluative statistics. RESULTS: The three models attain almost identical results, with negligible difference in accuracy. The "best"-performing model (Multinomial logistic classifier) achieved a 47.34% [SD 1.63] classification accuracy while the decision tree model achieved an almost comparable 45.82% [SD 1.69]. The three models achieved an average AUC of approximately 0.66 suggesting sufficient predictive signal at the four categorical variables selected. CONCLUSIONS: Machine-learning models give us a demonstrably effective tool to predict the recruited health workers' length of practice. These models can be adapted in future studies to incorporate other information beside demographic details such as information about placement location and income. Beyond the scope of predicting length of practice, this modelling technique will also allow strategic planning and optimization of public healthcare recruitment.

Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver.

Purpose To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver. Materials and Methods DLS for CT-based staging of liver fibrosis was created by using a development data set that included portal venous phase CT images in 7461 patients with pathologically confirmed liver fibrosis. The diagnostic performance of the DLS was evaluated in separate test data sets for 891 patients. The influence of patient characteristics and CT techniques on the staging accuracy of the DLS was evaluated by logistic regression analysis. In a subset of 421 patients, the diagnostic performance of the DLS was compared with that of the radiologist's assessment, aminotransferase-to-platelet ratio index (APRI), and fibrosis-4 index by using the area under the receiver operating characteristic curve (AUROC) and Obuchowski index. Results In the test data sets, the DLS had a staging accuracy of 79.4% (707 of 891) and an AUROC of 0.96, 0.97, and 0.95 for diagnosing significant fibrosis (F2-4), advanced fibrosis (F3-4), and cirrhosis (F4), respectively. At multivariable analysis, only pathologic fibrosis stage significantly affected the staging accuracy of the DLS (P = .016 and .013 for F1 and F2, respectively, compared with F4), whereas etiology of liver disease and CT technique did not. The DLS (Obuchowski index, 0.94) outperformed the radiologist's interpretation, APRI, and fibrosis-4 index (Obuchowski index range, 0.71-0.81; P ˂ .001) for staging liver fibrosis. Conclusion The deep learning system allows for accurate staging of liver fibrosis by using CT images. © RSNA, 2018 Online supplemental material is available for this article.

Acceptability of community-based adherence clubs among health facility staff in South Africa: a qualitative study.

BACKGROUND: Patient retention in care for HIV/AIDS is a critical challenge for antiretroviral treatment programs. Community-based adherence programs (CBAPs) as compared to health care facility-based adherence programs have been considered as one of the options to provide treatment maintenance support for groups of patients on antiretroviral therapy. Such an approach provides a way of enhancing self-management of the patient's condition. In addition, CBAPs have been implemented to support antiretroviral treatment expansion in resource-limited settings. CBAPs involve 30 patients that are allocated to a group and meet at either a facility or a community venue for less than an hour every 2 or 3 months depending on the supply of medication. Our study aimed to establish perceived challenges in moving adherence clubs from health facilities to communities. METHODS: A qualitative study was conducted in 39 clinics in Mpumalanga and Gauteng Provinces in South Africa between December 2015 and January 2016. Purposive sampling method was used to identify nurses, club managers, data capturers, pharmacists and pharmacy assistants who had been involved in facility-based treatment adherence clubs. Key-informant interviews were conducted. Also, semi-structured interviews were used and thematic content analysis was done. RESULTS: A total of 53 health care workers, 12 (22.6%) males and 41 (77.4%) females, participated in the study. Most of them 49 (92.5%) indicated that participating in community adherence clubs were a good idea. Reduction in waiting time at the health facilities, in defaulter rate, improvement in adherence to treatment as well as reduction in stigma were some of the perceived benefits. However, security of medication, storage conditions and transportation of the prepacked medication to the distribution sites were the areas of concern. CONCLUSION: Health care workers were agreeable to idea of the moving adherence clubs from health facilities to communities. Although some challenges were identified, these could be addressed by the key stakeholders. However, government and nongovernmental organizations need to exercise caution when transitioning to community-based adherence clubs.

Finding Common Ground: Environmental Ethics, Social Justice, and a Sustainable Path for Nature-Based Health Promotion.

Decades of research have documented continuous tension between anthropocentric needs and the environment's capacity to accommodate those needs and support basic human welfare. The way in which society perceives, manages, and ultimately utilizes natural resources can be influenced by underlying environmental ethics, or the moral relationship that humans share with the natural world. This discourse often centers on the complex interplay between the tangible and intangible benefits associated with nonhuman nature (e.g., green space), both of which are relevant to public health. When ecosystem degradation is coupled with socio-demographic transitions, additional concerns related to distributional equity and justice can arise. In this commentary, we explore how environmental ethics can inform the connection between the ecosystem services from green space and socially just strategies of health promotion.

Advancing Sustainability through Urban Green Space: Cultural Ecosystem Services, Equity, and Social Determinants of Health.

Urban green spaces provide an array of benefits, or ecosystem services, that support our physical, psychological, and social health. In many cases, however, these benefits are not equitably distributed across diverse urban populations. In this paper, we explore relationships between cultural ecosystem services provided by urban green space and the social determinants of health outlined in the United States Healthy People 2020 initiative. Specifically, we: (1) explore connections between cultural ecosystem services and social determinants of health; (2) examine cultural ecosystem services as nature-based health amenities to promote social equity; and (3) recommend areas for future research examining links between urban green space and public health within the context of environmental justice.

Facioscapulohumeral muscular dystrophy region gene 1 is a dynamic RNA-associated and actin-bundling protein.

FSHD region gene 1 (FRG1) is a dynamic nuclear and cytoplasmic protein that, in skeletal muscle, shows additional localization to the sarcomere. Maintaining appropriate levels of FRG1 protein is critical for muscular and vascular development in vertebrates; however, its precise molecular function is unknown. This study investigates the molecular functions of human FRG1, along with mouse FRG1 and Xenopus frg1, using molecular, biochemical, and cellular-biological approaches, to provide further insight into its roles in vertebrate development. The nuclear fraction of the endogenous FRG1 is localized in nucleoli, Cajal bodies, and actively transcribed chromatin; however, contrary to overexpressed FRG1, the endogenous FRG1 is not associated with nuclear speckles. We characterize the nuclear and nucleolar import of FRG1, the potential effect of phosphorylation, and its interaction with the importin karyopherin α2. Consistent with a role in RNA biogenesis, human FRG1 is associated with mRNA in vivo and invitro, interacts directly with TAP (Tip-associated protein; the major mRNA export receptor), and is a dynamic nuclear-cytoplasmic shuttling protein supporting a function for FRG1 in mRNA transport. Biochemically, we characterize FRG1 actin binding activity and show that the cytoplasmic pool of FRG1 is dependent on an intact actin cytoskeleton for its localization. These data provide the first biochemical activities (actin binding and RNA binding) for human FRG1 and the characterization of the endogenous human FRG1, together indicating that FRG1 is involved in multiple aspects of RNA biogenesis, including mRNA transport and, potentially, cytoplasmic mRNA localization.

Facioscapulohumeral muscular dystrophy (FSHD) region gene 1 (FRG1) is a dynamic nuclear and sarcomeric protein.

Facioscapulohumeral muscular dystrophy (FSHD) region gene 1 (FRG1) is a candidate gene for mediating FSHD pathophysiology, however, very little is known about the endogenous FRG1 protein. This study uses immunocytochemistry (ICC) and histology to provide insight into FRG1's role in vertebrate muscle development and address its potential involvement in FSHD pathophysiology. In cell culture, primary myoblast/myotube cultures, and mouse and human muscle sections, FRG1 showed distinct nuclear and cytoplasmic localizations and nuclear shuttling assays indicated the subcellular pools of FRG1 are linked. During myoblast differentiation, FRG1's subcellular distribution changed dramatically with FRG1 eventually associating with the matured Z-discs. This Z-disc localization was confirmed using isolated mouse myofibers and found to be maintained in adult human skeletal muscle biopsies. Thus, FRG1 is not likely involved in the initial assembly and alignment of the Z-disc but may be involved in sarcomere maintenance or signaling. Further analysis of human tissue showed FRG1 is strongly expressed in arteries, veins, and capillaries, the other prominently affected tissue in FSHD. Overall, we show that in mammalian cells, FRG1 is a dynamic nuclear and cytoplasmic protein, however in muscle, FRG1 is also a developmentally regulated sarcomeric protein suggesting FRG1 may perform a muscle-specific function. Thus, FRG1 is the only FSHD candidate protein linked to the muscle contractile machinery and may address why the musculature and vasculature are specifically susceptible in FSHD.