Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Are non-slip socks really 'non-slip'? An analysis of slip resistance

Background. Non-slip socks have been suggested as a means of preventing accidental falls due to slips. This study compared the relative slip resistance of commercially available non-slip socks with other foot conditions, namely bare feet, compression stockings and conventional socks, in order to determine any traction benefit. Methods. Phase one involved slip resistance testing of two commercially available non-slip socks and one compression-stocking sample through an independent blinded materials testing laboratory using a Wet Pendulum Test. Phase two of the study involved in-situ testing among healthy adult subjects (n = 3). Subjects stood unsupported on a variable angle, inclined platform topped with hospital grade vinyl, in a range of foot conditions (bare feet, non-slip socks, conventional socks and compression stockings). Inclination was increased incrementally for each condition until slippage of any magnitude was detected. The platform angle was monitored using a spatial orientation tracking sensor and slippage point was recorded on video. Results. Phase one results generated through Wet Pendulum Test suggested that non-slip socks did not offer better traction than compression stockings. However, in phase two, slippage in compression stockings was detected at the lowest angles across all participants. Amongst the foot conditions tested, barefoot conditions produced the highest slip angles for all participants indicating that this foot condition provided the highest slip resistance. Conclusion. It is evident that bare feet provide better slip resistance than non-slip socks and therefore might represent a safer foot condition. This study did not explore whether traction provided by bare feet was comparable to 'optimal' footwear such as shoes. However, previous studies have associated barefoot mobilisation with increased falls. Therefore, it is suggested that all patients continue to be encouraged to mobilise in appropriate, well-fitting shoes whilst in hospital. Limitations of this study in relation to the testing method, participant group and sample size are discussed

Primary spinal cord tumors of childhood: effects of clinical presentation, radiographic features, and pathology on survival

To determine the relationship between clinical presentation, radiographic features, pathology, and treatment on overall survival of newly diagnosed pediatric primary spinal cord tumors (PSCT). Retrospective analysis of all previously healthy children with newly diagnosed PSCT at a single institution from 1995 to present was performed. Twenty-five pediatric patients (15 boys, average 7.9 years) were diagnosed with PSCT. Presenting symptoms ranged from 0.25 to 60 months (average 7.8 months). Symptom duration was significantly shorter for high grade tumors (average 1.65 months) than low grade tumors (average 11.2 months) (P = 0.05). MRI revealed tumor (8 cervical, 17 thoracic, 7 lumbar, 7 sacral) volumes of 98–94,080 mm3 (average 19,474 mm3). Homogeneous gadolinium enhancement on MRI correlated with lower grade pathology (P = 0.003). There was no correlation between tumor grade and volume (P = 0.63) or edema (P = 0.36) by MRI analysis. Median survival was 53 months and was dependent on tumor grade (P = 0.05) and gross total resection (P = 0.01) but not on gender (P = 0.49), age of presentation (P = 0.82), duration of presenting symptoms (P = 0.33), or adjuvant therapies (P = 0.17). Stratified Kaplan–Meier analysis confirmed the association between degree of resection and survival after controlling for tumor grade (P = 0.01). MRI homogeneous gadolinium enhancement patterns may be helpful in distinguishing low grade from high grade spinal cord malignancies. While tumor grade and gross total resection rather than duration of symptoms correlated with survival in our series, greater than one-third of patients had reported symptoms greater than 6 months duration prior to diagnosis

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution