Myostatin and the skeletal muscle atrophy and hypertrophy signaling pathways

Myostatin, a member of the transforming growth factor-β superfamily, is a potent negative regulator of skeletal muscle growth and is conserved in many species, from rodents to humans. Myostatin inactivation can induce skeletal muscle hypertrophy, while its overexpression or systemic administration causes muscle atrophy. As it represents a potential target for stimulating muscle growth and/or preventing muscle wasting, myostatin regulation and functions in the control of muscle mass have been extensively studied. A wealth of data strongly suggests that alterations in skeletal muscle mass are associated with dysregulation in myostatin expression. Moreover, myostatin plays a central role in integrating/mediating anabolic and catabolic responses. Myostatin negatively regulates the activity of the Akt pathway, which promotes protein synthesis, and increases the activity of the ubiquitin–proteasome system to induce atrophy. Several new studies have brought new information on how myostatin may affect both ribosomal biogenesis and translation efficiency of specific mRNA subclasses. In addition, although myostatin has been identified as a modulator of the major catabolic pathways, including the ubiquitin–proteasome and the autophagy–lysosome systems, the underlying mechanisms are only partially understood. The goal of this review is to highlight outstanding questions about myostatin-mediated regulation of the anabolic and catabolic signaling pathways in skeletal muscle. Particular emphasis has been placed on (1) the cross-regulation between myostatin, the growth-promoting pathways and the proteolytic systems; (2) how myostatin inhibition leads to muscle hypertrophy; and (3) the regulation of translation by myostatin.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Mutations in NMNAT1 cause Leber congenital amaurosis and identify a new disease pathway for retinal degeneration

Leber congenital amaurosis (LCA) is a blinding retinal disease that presents within the first year after birth. Using exome sequencing, we identified mutations in the nicotinamide adenine dinucleotide (NAD) synthase gene NMNAT1 encoding nicotinamide mononucleotide adenylyltransferase 1 in eight families with LCA, including the family in which LCA was originally linked to the LCA9 locus. Notably, all individuals with NMNAT1 mutations also have macular colobomas, which are severe degenerative entities of the central retina (fovea) devoid of tissue and photoreceptors. Functional assays of the proteins encoded by the mutant alleles identified in our study showed that the mutations reduce the enzymatic activity of NMNAT1 in NAD biosynthesis and affect protein folding. Of note, recent characterization of the slow Wallerian degeneration (Wld(s)) mouse model, in which prolonged axonal survival after injury is observed, identified NMNAT1 as a neuroprotective protein when ectopically expressed. Our findings identify a new disease mechanism underlying LCA and provide the first link between endogenous NMNAT1 dysfunction and a human nervous system disorder.     

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.     

Identification of low-frequency variants associated with gout and serum uric acid levels

We tested 16 million SNPs, identified through whole-genome sequencing of 457 Icelanders, for association with gout and serum uric acid levels. Genotypes were imputed into 41,675 chip-genotyped Icelanders and their relatives, for effective sample sizes of 968 individuals with gout and 15,506 individuals for whom serum uric acid measurements were available. We identified a low-frequency missense variant (c.1580C>G) in ALDH16A1 associated with gout (OR = 3.12, P = 1.5 × 10(-16), at-risk allele frequency = 0.019) and serum uric acid levels (effect = 0.36 s.d., P = 4.5 × 10(-21)). We confirmed the association with gout by performing Sanger sequencing on 6,017 Icelanders. The association with gout was stronger in males relative to females. We also found a second variant on chromosome 1 associated with gout (OR = 1.92, P = 0.046, at-risk allele frequency = 0.986) and serum uric acid levels (effect = 0.48 s.d., P = 4.5 × 10(-16)). This variant is close to a common variant previously associated with serum uric acid levels. This work illustrates how whole-genome sequencing data allow the detection of associations between low-frequency variants and complex traits.     

Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3

We performed a genome-wide association study of melanoma in a discovery cohort of 2,168 Australian individuals with melanoma and 4,387 control individuals. In this discovery phase, we confirm several previously characterized melanoma-associated loci at MC1R, ASIP and MTAP-CDKN2A. We selected variants at nine loci for replication in three independent case-control studies (Europe: 2,804 subjects with melanoma, 7,618 control subjects; United States 1: 1,804 subjects with melanoma, 1,026 control subjects; United States 2: 585 subjects with melanoma, 6,500 control subjects). The combined meta-analysis of all case-control studies identified a new susceptibility locus at 1q21.3 (rs7412746, P = 9.0 × 10(-11), OR in combined replication cohorts of 0.89 (95% CI 0.85-0.95)). We also show evidence suggesting that melanoma associates with 1q42.12 (rs3219090, P = 9.3 × 10(-8)). The associated variants at the 1q21.3 locus span a region with ten genes, and plausible candidate genes for melanoma susceptibility include ARNT and SETDB1. Variants at the 1q21.3 locus do not seem to be associated with human pigmentation or measures of nevus density.     

Genome-wide association study reveals three susceptibility loci for common migraine in the general population

Migraine is a common, heterogeneous and heritable neurological disorder. Its pathophysiology is incompletely understood, and its genetic influences at the population level are unknown. In a population-based genome-wide analysis including 5,122 migraineurs and 18,108 non-migraineurs, rs2651899 (1p36.32, PRDM16), rs10166942 (2q37.1, TRPM8) and rs11172113 (12q13.3, LRP1) were among the top seven associations (P < 5 × 10(-6)) with migraine. These SNPs were significant in a meta-analysis among three replication cohorts and met genome-wide significance in a meta-analysis combining the discovery and replication cohorts (rs2651899, odds ratio (OR) = 1.11, P = 3.8 × 10(-9); rs10166942, OR = 0.85, P = 5.5 × 10(-12); and rs11172113, OR = 0.90, P = 4.3 × 10(-9)). The associations at rs2651899 and rs10166942 were specific for migraine compared with non-migraine headache. None of the three SNP associations was preferential for migraine with aura or without aura, nor were any associations specific for migraine features. TRPM8 has been the focus of neuropathic pain models, whereas LRP1 modulates neuronal glutamate signaling, plausibly linking both genes to migraine pathophysiology.