Macroorchidism in FMR1 knockout mice is caused by increased Sertoli cell proliferation during testicular development

The fragile X syndrome is the most frequent hereditary form of mental retardation. This X-linked disorder is, in most cases, caused by an unstable and expanding trinucleotide CGG repeat located in the 5'-untranslated region of the gene involved, the fragile X mental retardation 1 (FMR1) gene. Expansion of the CGG repeat to a length of more than 200 trinucleotides results in silencing of the FMR1 gene promoter and, thus, in an inactive gene. The clinical features of male fragile X patients include mental retardat

The changing microRNA landscape by color and cloudiness:a cautionary tale for nipple aspirate fluid biomarker analysis

Purpose: Investigation of nipple aspirate fluid (NAF)-based microRNAs (miRNAs) as a potential screening tool for women at increased risk of developing breast cancer is the scope of our research. While aiming to identify discriminating NAF-miRNAs between women with different mammographic densities, we were confronted with an unexpected confounder: NAF sample appearance. Here we report and alert for the impact of NAF color and cloudiness on miRNA assessment. Methods: Seven classes of NAF colors coupled with cloudiness appearance were established. Using 173 NAF samples from 154 healthy women (19 samples were bilaterally collected), the expression of 14 target and 2 candidate endogenous control (EC) miRNAs was investigated using Taqman Advanced miRNA assays to identify significant differential expression patterns between color-cloudiness classes. Inter- and intra-individual variation of miRNA expression was analyzed using the coefficient of variation (CV). Results: We found that between the seven NAF classes, fold change miRNA expression differences ranged between 2.4 and 19.6 depending on the interrogated miRNA. Clear NAF samples exhibited higher miRNA expression levels compared to cloudy NAF samples with fold change differences ranging between 1.1 and 6.2. Inter-individual and intra-individual miRNA expression was fairly stable (CV &lt; 15 %), but nevertheless impacted by NAF sample appearance. Within NAF classes, inter-individual variation was largest for green samples (CV 6-15 %) and smallest for bloody samples (CV 2-6 %). Conclusions: Our data indicate that NAF color and cloudiness influence miRNA expression and should, therefore, be systematically registered using an objective color classification system. Given that sample appearance is an inherent feature of NAF, these variables should be statistically controlled for in multivariate data analyses. This cautionary note and recommendations could be of value beyond the field of NAF-miRNAs, given that variability in sample color and cloudiness is likewise observed in liquid biopsies such as urine, cerebrospinal fluid and sputum, and could thereby influence the levels of miRNAs and other biomarkers.</p

Generalized glycogen storage and cardiomegaly in a knockout mouse model of Pompe disease

Glycogen storage disease type II (GSDII; Pompe disease), caused by inherited deficiency of acid alpha-glucosidase, is a lysosomal disorder affecting heart and skeletal muscles. A mouse model of this disease was obtained by targeted disruption of the murine acid alpha-glucosidase gene (Gaa) in embryonic stem cells. Homozygous knockout mice (Gaa -/-) lack Gaa mRNA and have a virtually complete acid alpha-glucosidase deficiency. Glycogen-containing lysosomes are detected soon after birth in liver, heart and skeletal muscle cells. By 13 weeks of age, large focal deposits of glycogen have formed. Vacuolar spaces stain positive for acid phosphatase as a sign of lysosomal pathology. Both male and female knockout mice are fertile and can be intercrossed to produce progeny. The first born knockout mice are at present 9 months old. Overt clinical symptoms are still absent, but the heart is typically enlarged and the electrocardiogram is abnormal. The mouse model will help greatly to understand the pathogenic mechanism of GSDII and is a valuable instrument to explore the efficacy of different therapeutic interventions

A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Meta-Analysis for Genome-Wide Association Study Identifies Multiple Variants at the BIN1 Locus Associated with Late-Onset Alzheimer's Disease

Recent GWAS studies focused on uncovering novel genetic loci related to AD have revealed associations with variants near CLU, CR1, PICALM and BIN1. In this study, we conducted a genome-wide association study in an independent set of 1034 cases and 1186 controls using the Illumina genotyping platforms. By coupling our data with available GWAS datasets from the ADNI and GenADA, we replicated the original associations in both PICALM (rs3851179) and CR1 (rs3818361). The PICALM variant seems to be non-significant after we adjusted for APOE e4 status. We further tested our top markers in 751 independent cases and 751 matched controls. Besides the markers close to the APOE locus, a marker (rs12989701) upstream of BIN1 locus was replicated and the combined analysis reached genome-wide significance level (p = 5E-08). We combined our data with the published Harold et al. study and meta-analysis with all available 6521 cases and 10360 controls at the BIN1 locus revealed two significant variants (rs12989701, p = 1.32E-10 and rs744373, p = 3.16E-10) in limited linkage disequilibrium (r2 = 0.05) with each other. The independent contribution of both SNPs was supported by haplotype conditional analysis. We also conducted multivariate analysis in canonical pathways and identified a consistent signal in the downstream pathways targeted by Gleevec (P = 0.004 in Pfizer; P = 0.028 in ADNI and P = 0.04 in GenADA). We further tested variants in CLU, PICALM, BIN1 and CR1 for association with disease progression in 597 AD patients where longitudinal cognitive measures are sufficient. Both the PICALM and CLU variants showed nominal significant association with cognitive decline as measured by change in Clinical Dementia Rating-sum of boxes (CDR-SB) score from the baseline but did not pass multiple-test correction. Future experiments will help us better understand potential roles of these genetic loci in AD pathology

Comprehensive Genotyping in Two Homogeneous Graves' Disease Samples Reveals Major and Novel HLA Association Alleles

BACKGROUND: Graves' disease (GD) is the leading cause of hyperthyroidism and thyroid eye disease inherited as a complex trait. Although geoepidemiology studies showed relatively higher prevalence of GD in Asians than in Caucasians, previous genetic studies were contradictory concerning whether and/or which human leukocyte antigen (HLA) alleles are associated with GD in Asians. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a case-control association study (499 unrelated GD cases and 504 controls) and a replication in an independent family sample (419 GD individuals and their 282 relatives in 165 families). To minimize genetic and phenotypic heterogeneity, we included only ethnic Chinese Han population in Taiwan and excluded subjects with hypothyroidism. We performed direct and comprehensive genotyping of six classical HLA loci (HLA-A, -B, -C, -DPB1, -DQB1 and -DRB1) to 4-digit resolution. Combining the data of two sample populations, we found that B*46:01 (odds ratio under dominant model [OR]  = 1.33, Bonferroni corrected combined P [P(Bc)]  = 1.17 x 10⁻²), DPB1*05:01 (OR  = 2.34, P(Bc) = 2.58 x 10⁻¹⁰), DQB1*03:02 (OR  = 0.62, P(Bc)  = 1.97 x 10⁻²), DRB1*15:01 (OR  = 1.68, P(Bc) = 1.22 x 10⁻²) and DRB1*16:02 (OR  = 2.63, P(Bc)  = 1.46 x 10⁻⁵) were associated with GD. HLA-DPB1*05:01 is the major gene of GD in our population and singly accounts for 48.4% of population-attributable risk. CONCLUSIONS/SIGNIFICANCE: These GD-associated alleles we identified in ethnic Chinese Hans, and those identified in other Asian studies, are totally distinct from the known associated alleles in Caucasians. Identification of population-specific association alleles is the critical first step for individualized medicine. Furthermore, comparison between different susceptibility/protective alleles across populations could facilitate generation of novel hypothesis about GD pathophysiology and indicate a new direction for future investigation