Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identified 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n=48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p=4*10-17), arthritis (GDF5 p=4*10-13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, hematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.

AbstractLow muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.

BACKGROUND: Aging is characterized by chronic inflammation plus loss of muscle mass and strength, termed sarcopenia. Human leukocyte antigen (HLA) types are drivers of autoimmune disease, although with limited penetrance. We tested whether autoimmune diagnoses are associated with sarcopenia, and whether HLA types and related genetic variants are associated with sarcopenia in autoimmune disease-free older people. METHODS: Data were collected from 181,301 UK Biobank European descent volunteers aged 60-70 with measured hand grip strength and impedance. Logistic regression analysis estimated HLA type and sarcopenia associations, adjusted for confounders and multiple testing. RESULTS: Having any autoimmune diagnosis was associated with sarcopenia (odds ratio [OR] 1.83, 95% confidence interval (CI) 1.74-1.92, p = 4.0*10-125). After excluding autoimmune diagnoses, 6 of 100 HLA types (allele frequency >1%) were associated with sarcopenia (low grip strength and muscle mass). Having two HLA-DQA1*03:01 alleles increased odds of sarcopenia by 19.3% (OR 1.19, CI 1.09-1.29, p = 2.84*10-5), compared to no alleles. Having ≥6 of the 12 HLA alleles increased sarcopenia odds by 23% (OR 1.23, CI 1.12-1.35, p = 7.28*10-6). of 658 HLA region non-coding genetic variants previously implicated in disease, 4 were associated with sarcopenia, including rs41268896 and rs29268645 (OR 1.08, CI 1.05-1.11, p = 1.06*10-8 and 1.07, CI 1.04-1.09, p = 1.5*10-6, respectively). Some HLA associations with sarcopenia were greater in female participants. CONCLUSION: Autoimmune diagnoses are strongly associated with sarcopenia in 60- to 70-year olds. Variation in specific HLA types and non-coding single nucleotide polymorphisms is also associated with sarcopenia in older carriers free of diagnosed autoimmune diseases. Patients with sarcopenia might benefit from targeted treatment of autoimmune processes.

OBJECTIVE: Rare genetic disorders resulting in prenatal or neonatal death are genetically heterogeneous, but testing is often limited by the availability of fetal DNA, leaving couples without a potential prenatal test for future pregnancies. We describe our novel strategy of exome sequencing parental DNA samples to diagnose recessive monogenic disorders in an audit of the first 50 couples referred. METHOD: Exome sequencing was carried out in a consecutive series of 50 couples who had 1 or more pregnancies affected with a lethal or prenatal-onset disorder. In all cases, there was insufficient DNA for exome sequencing of the affected fetus. Heterozygous rare variants (MAF 

Copy number variants (CNV) are a major cause of disease, with over 30,000 reported in the DECIPHER database. To use read depth data from targeted Next Generation Sequencing (NGS) panels to identify CNVs with the highest degree of sensitivity, it is necessary to account for biases inherent in the data. GC content and ambiguous mapping due to repetitive sequence elements and pseudogenes are the principal components of technical variability. In addition, the algorithms used favour the detection of multi-exon CNVs, and rely on suitably matched normal dosage samples for comparison. We developed a calling strategy that subdivides target intervals, and uses pools of historical control samples to overcome these limitations in a clinical diagnostic laboratory. We compared our enhanced strategy with an unmodified pipeline using the R software package ExomeDepth, using a cohort of 109 heterozygous CNVs (91 deletions, 18 duplications in 26 genes), including 25 single exon CNVs. The unmodified pipeline detected 104/109 CNVs, giving a sensitivity of 89.62% to 98.49% at the 95% confidence interval. The detection of all 109 CNVs by our enhanced method demonstrates 95% confidence the sensitivity is ≥96.67%, allowing NGS read depth analysis to be used for CNV detection in a clinical diagnostic setting.

Neonatal diabetes is frequently part of a complex syndrome with extrapancreatic features: 18 genes causing syndromic neonatal diabetes have been identified to date. There are still patients with neonatal diabetes who have novel genetic syndromes. We performed exome sequencing in a patient and his unrelated, unaffected parents to identify the genetic etiology of a syndrome characterized by neonatal diabetes, sensorineural deafness, and congenital cataracts. Further testing was performed in 311 patients with diabetes diagnosed before 1 year of age in whom all known genetic causes had been excluded. We identified 5 patients, including the initial case, with three heterozygous missense mutations in WFS1 (4/5 confirmed de novo). They had diabetes diagnosed before 12 months (2 before 6 months) (5/5), sensorineural deafness diagnosed soon after birth (5/5), congenital cataracts (4/5), and hypotonia (4/5). In vitro studies showed that these WFS1 mutations are functionally different from the known recessive Wolfram syndrome-causing mutations, as they tend to aggregate and induce robust endoplasmic reticulum stress. Our results establish specific dominant WFS1 mutations as a cause of a novel syndrome including neonatal/infancy-onset diabetes, congenital cataracts, and sensorineural deafness. This syndrome has a discrete pathophysiology and differs genetically and clinically from recessive Wolfram syndrome.

BACKGROUND: Legionella pneumophila is an opportunistic pathogen of humans where the source of infection is usually from contaminated man-made water systems. When an outbreak of Legionnaires' disease caused by L. pneumophila occurs, it is necessary to discover the source of infection. A seven allele sequence-based typing scheme (SBT) has been very successful in providing the means to attribute outbreaks of L. pneumophila to a particular source or sources. Particular sequence types described by this scheme are known to exhibit specific phenotypes. For instance some types are seen often in clinical cases but are rarely isolated from the environment and vice versa. of those causing human disease some types are thought to be more likely to cause more severe disease. It is possible that the genetic basis for these differences are vertically inherited and associated with particular genetic lineages within the population. In order to provide a framework within which to test this hypothesis and others relating to the population biology of L. pneumophila, a set of genomes covering the known diversity of the organism is required. RESULTS: Firstly, this study describes a means to group L. pneumophila strains into pragmatic clusters, using a methodology that takes into consideration the genetic forces operating on the population. These clusters can be used as a standardised nomenclature, so those wishing to describe a group of strains can do so. Secondly, the clusters generated from the first part of the study were used to select strains rationally for whole genome sequencing (WGS). The data generated was used to compare phylogenies derived from SBT and WGS. In general the SBT sequence type (ST) accurately reflects the whole genome-based genotype. Where there are exceptions and recombination has resulted in the ST no longer reflecting the genetic lineage described by the whole genome sequence, the clustering technique employed detects these sequence types as being admixed, indicating their mixed inheritance. CONCLUSIONS: We conclude that SBT is usually a good proxy for the genetic lineage described by the whole genome, and therefore utility of SBT is still suitable until the technology and economics of high throughput sequencing reach the point where routine WGS of L. pneumophila isolates for outbreak investigation is feasible.