Sepsis continues to be a major cause of death, disability, and health-care expenditure worldwide. Despite evidence suggesting that host genetics can influence sepsis outcomes, no specific loci have yet been convincingly replicated. The aim of this study was to identify genetic variants that influence sepsis survival.
We did a genome-wide association study in three independent cohorts of white adult patients admitted to intensive care units with sepsis, severe sepsis, or septic shock (as defined by the International Consensus Criteria) due to pneumonia or intra-abdominal infection (cohorts 1–3, n=2534 patients). The primary outcome was 28 day survival. Results for the cohort of patients with sepsis due to pneumonia were combined in a meta-analysis of 1553 patients from all three cohorts, of whom 359 died within 28 days of admission to the intensive-care unit. The most significantly associated single nucleotide polymorphisms (SNPs) were genotyped in a further 538 white patients with sepsis due to pneumonia (cohort 4), of whom 106 died.
In the genome-wide meta-analysis of three independent pneumonia cohorts (cohorts 1–3), common variants in the FER gene were strongly associated with survival (p=9·7 × 10−8). Further genotyping of the top associated SNP (rs4957796) in the additional cohort (cohort 4) resulted in a combined p value of 5·6 × 10−8 (odds ratio 0·56, 95% CI 0·45–0·69). In a time-to-event analysis, each allele reduced the mortality over 28 days by 44% (hazard ratio for death 0·56, 95% CI 0·45–0·69; likelihood ratio test p=3·4 × 10−9, after adjustment for age and stratification by cohort). Mortality was 9·5% in patients carrying the CC genotype, 15·2% in those carrying the TC genotype, and 25·3% in those carrying the TT genotype. No significant genetic associations were identified when patients with sepsis due to pneumonia and intra-abdominal infection were combined.
We have identified common variants in the FER gene that associate with a reduced risk of death from sepsis due to pneumonia. The FER gene and associated molecular pathways are potential novel targets for therapy or prevention and candidates for the development of biomarkers for risk stratification.
European Commission and the Wellcome Trust.
Small interfering RNA (siRNA) mediated gene silencing has been utilized as a powerful molecular tool to study the functional significance of a specific protein. However, due to transient gene silencing and insufficient transfection efficiency, this approach can be problematic in primary cell culture such as vascular smooth muscle cells. To overcome this weakness, we utilized an adenoviral-encoded microRNA (miRNA)-embedded siRNA “mi/siRNA”-based RNA interference. Here, we report the results of silencing a disintegrin and metalloprotease 17 (ADAM17) in cultured rat vascular smooth muscle cells and its functional mechanism in angiotensin II signal transduction. 3 distinct mi/siRNA sequences targeting rat ADAM17 were inserted into pAd/CMV/V5-DEST and adenoviral solutions were obtained. Nearly 90% silencing of ADAM17 was achieved when vascular smooth muscle cells were infected with 100 multiplicity of infection of each ADAM17 mi/siRNA encoding adenovirus for 3 days. mi/siRNA-ADAM17 but not mi/siRNA-control inhibited angiotensin II-induced epidermal growth factor receptor trans-activation and subsequent extracellular signal-regulated kinase activation and hypertrophic response in the cells. mi/siRNA-ADAM17 also inhibited angiotensin II-induced heparin-binding epidermal growth factor-like factor shedding. This inhibition was rescued with co-infection of adenovirus encoding mouse ADAM17 but not by its cytosolic domain deletion mutant or cytosolic Y702F mutant. As expected, angiotensin II induced tyrosine phosphorylation of ADAM17 in the cells. In conclusion, ADAM17 activation via its tyrosine phosphorylation contributes to heparin-binding epidermal growth factor-like factor shedding and subsequent growth promoting signals induced by angiotensin II in vascular smooth muscle cells. An artificial mi/siRNA-based adenoviral approach appears to be a reliable gene-silencing strategy for signal transduction research in primary cultured vascular cells.
ADAM17; Epidermal Growth Factor Receptor; Angiotensin II Type 1 Receptor; Signal Transduction; Vascular Biology
The Max-interacting protein Mnt is a transcriptional repressor that can antagonize the transcriptional and proliferation-related activities of Myc. Here, we tested the hypothesis that Mnt is a negative regulator of pathological vascular remodeling.
Adenovirus encoding Mnt or control GFP was infected to cultured rat vascular smooth muscle cells (VSMC) and carotid arteries after a balloon angioplasty.
In VSMC, adenoviral gene transfer of Mnt suppressed angiotensin II-induced protein expression of early growth response protein-1 (Egr1) and its promoter activation. Mnt adenovirus did not interfere with upstream signaling of angiotensin II. Angiotensin II-induced protein accumulation in VSMC was inhibited by Mnt adenovirus. Mnt adenovirus also inhibited platelet-derived growth factor-induced VSMC proliferation. Moreover, Mnt adenovirus prevented neointima formation in response to arterial injury. The adenoviral Mnt gene transfer also prevented Egr1 induction in neointima.
These data identify Mnt as a previously unrecognized negative regulator of pathological vascular remodeling.
transcriptional repressor; angioplasty; gene therapy; restenosis; signal transduction
The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1,924 diabetic cases and 2,938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3,757 additional cases and 5,346 controls, and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insights into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.
Interferon-inducible transmembrane proteins 1, 2, and 3 (IFITM 1,2, and 3) are viral restriction factors that mediate cellular resistance to several viruses. We have genotyped a possible splice-site altering single-nucleotide polymorphism (rs12252) in the IFITM3 gene in 34 patients with H1N1 influenza and severe pneumonia, and >5000 individuals comprising patients with community-acquired mild lower respiratory tract infection and matched controls of Caucasian ancestry. We found evidence of an association between rs12252 rare allele homozygotes and susceptibility to mild influenza (in patients attending primary care) but could not confirm a previously reported association between this single-nucleotide polymorphism and susceptibility to severe H1N1 infection.
genetics; H1N1; Influenza; LRTI; infectious disease; IFITM3; association study; Virus
We have identified gene fusions of polyamine biosynthetic enzymes S-adenosylmethionine decarboxylase (AdoMetDC, speD) and aminopropyltransferase (speE) orthologues in diverse bacterial phyla. Both domains are functionally active and we demonstrate the novel de novo synthesis of the triamine spermidine from the diamine putrescine by fusion enzymes from β-proteobacterium Delftia acidovorans and δ-proteobacterium Syntrophus aciditrophicus, in a ΔspeDE gene deletion strain of Salmonella enterica sv. Typhimurium. Fusion proteins from marine α-proteobacterium Candidatus Pelagibacter ubique, actinobacterium Nocardia farcinica, chlorobi species Chloroherpeton thalassium, and β-proteobacterium Delftia acidovorans each produce a different profile of non-native polyamines including sym-norspermidine when expressed in Escherichia coli. The different aminopropyltransferase activities together with phylogenetic analysis confirm independent evolutionary origins for some fusions. Comparative genomic analysis strongly indicates that gene fusions arose by merger of adjacent open reading frames. Independent fusion events, and horizontal and vertical gene transfer contributed to the scattered phyletic distribution of the gene fusions. Surprisingly, expression of fusion genes in E. coli and S. Typhimurium revealed novel latent spermidine catabolic activity producing non-native 1,3-diaminopropane in these species. We have also identified fusions of polyamine biosynthetic enzymes agmatine deiminase and N-carbamoylputrescine amidohydrolase in archaea, and of S-adenosylmethionine decarboxylase and ornithine decarboxylase in the single-celled green alga Micromonas.
evolution; gene fusion; polyamine; spermidine; S-adenosylmethionine decarboxylase; aminopropyltransferase
Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.
Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations.
From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ∼212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10−8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations.
Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.
Human height is a classic, highly heritable quantitative trait. To begin to identify genetic variants influencing height, we examined genome-wide association data from 4,921 individuals. Common variants in the HMGA2 oncogene, exemplified by rs1042725, were associated with height (P = 4 × 10−8). HMGA2 is also a strong biological candidate for height, as rare, severe mutations in this gene alter body size in mice and humans, so we tested rs1042725 in additional samples. We confirmed the association in 19,064 adults from four further studies (P = 3 × 10−11, overall P = 4 × 10−16, including the genome-wide association data). We also observed the association in children (P = 1 × 10−6, N = 6,827) and a tall/short case-control study (P = 4 × 10−6, N = 3,207). We estimate that rs1042725 explains ~0.3% of population variation in height (~0.4 cm increased adult height per C allele). There are few examples of common genetic variants reproducibly associated with human quantitative traits; these results represent, to our knowledge, the first consistently replicated association with adult and childhood height.
By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combinedP < 5 × 10−8. These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.
Given their involvement in processes necessary for life, mitochondrial damage and subsequent dysfunction can lead to a wide range of human diseases. Previous studies of both animal models and humans have suggested that PARL, presenilins-associated rhomboid-like protein, is a key regulator of mitochondrial integrity and function, and plays a role in cellular apoptosis. As a surrogate measure of mitochondrial integrity, we previously measured mitochondrial content in a Caucasian population consisting of large extended pedigrees, with results highlighting a substantial genetic component to this trait. To assess the influence of variation in the PARL gene on mitochondrial content, we re-sequenced 6.5kb of the gene, identifying 16 SNPs and genotyped these in 1,031 of these Caucasian individuals, distributed across 162 families. Statistical genetic analysis revealed that one promoter variant, T-191C, exhibited significant effects (after correction for multiple testing) on mitochondrial content levels. Comparison of the transcription factor binding characteristics of the T-191C promoter SNP by EMSA indicates preferential binding of nuclear factors to the T allele, suggesting functional variation in PARL expression. These results suggest that genetic variation within PARL influences mitochondrial abundance and integrity.
mitochondrial DNA; association; mitochondrial function/dysfunction; genotyping; sequencing
Digenic causes of human disease are rarely reported. Insulin via its receptor, which is encoded by INSR, plays a key role in both metabolic and growth signaling pathways. Heterozygous INSR mutations are the most common cause of monogenic insulin resistance. However, growth retardation is only reported with homozygous or compound heterozygous mutations. We describe a novel translocation [t(7,19)(p15.2;p13.2)] cosegregating with insulin resistance and pre- and postnatal growth deficiency. Chromosome translocations present a unique opportunity to identify modifying loci; therefore, our objective was to determine the mutational mechanism resulting in this complex phenotype.
RESEARCH DESIGN AND METHODS
Breakpoint mapping was performed by fluorescence in situ hybridization (FISH) on patient chromosomes. Sequencing and gene expression studies of disrupted and adjacent genes were performed on patient-derived tissues.
Affected individuals had increased insulin, C-peptide, insulin–to–C-peptide ratio, and adiponectin levels consistent with an insulin receptoropathy. FISH mapping established that the translocation breakpoints disrupt INSR on chromosome 19p15.2 and CHN2 on chromosome 7p13.2. Sequencing demonstrated INSR haploinsufficiency accounting for elevated insulin levels and dysglycemia. CHN2 encoding β-2 chimerin was shown to be expressed in insulin-sensitive tissues, and its disruption was shown to result in decreased gene expression in patient-derived adipose tissue.
We present a likely digenic cause of insulin resistance and growth deficiency resulting from the combined heterozygous disruption of INSR and CHN2, implicating CHN2 for the first time as a key element of proximal insulin signaling in vivo.
Genome-wide association studies have been successful in finding common variants influencing common traits. However, these associations only account for a fraction of trait heritability. There has been a shift in the field towards studying low frequency and rare variants, which are now widely recognised as putative complex trait determinants. Despite this increasing focus on examining the role of low frequency and rare variants in complex disease susceptibility, there is a lack of user-friendly analytical packages implementing powerful association tests for the analysis of rare variants.
We have developed two software tools, CCRaVAT (Case-Control Rare Variant Analysis Tool) and QuTie (Quantitative Trait), which enable efficient large-scale analysis of low frequency and rare variants. Both programs implement a collapsing method examining the accumulation of low frequency and rare variants across a locus of interest that has more power than single variant analysis. CCRaVAT carries out case-control analyses whereas QuTie has been developed for continuous trait analysis.
CCRaVAT and QuTie are easy to use software tools that allow users to perform genome-wide association analysis on low frequency and rare variants for both binary and quantitative traits. The software is freely available and provides the genetics community with a resource to perform association analysis on rarer genetic variants.
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5m genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N≤71,225 European ancestry, N=12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N=29,136). We identified association between systolic or diastolic blood pressure and common variants in 8 regions near the CYP17A1 (P=7×10−24), CYP1A2 (P=1×10−23), FGF5 (P=1×10−21), SH2B3 (P=3×10−18), MTHFR (P=2×10−13), c10orf107 (P=1×10−9), ZNF652 (P=5×10−9) and PLCD3 (P=1×10−8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
Genome-wide association studies (GWAS) conducted using commercial single nucleotide polymorphisms (SNP) arrays have proven to be a powerful tool for the detection of common disease susceptibility variants. However, their utility for the detection of lower frequency variants is yet to be practically investigated. Here we describe the application of a rare variant collapsing method to a large genome-wide SNP dataset, the Wellcome Trust Case Control Consortium rheumatoid arthritis (RA) GWAS. We partitioned the data into gene-centric bins and collapsed genotypes of low frequency variants (defined here as MAF ≤0.05) into a single count coupled with univariate analysis. We then prioritised gene regions for further investigation in an independent cohort of 3,355 cases and 2,427 controls based on rare variant signal p value and prior evidence to support involvement in RA. A total of 14,536 gene bins were investigated in the primary analysis and signals mapping to the TNFAIP3 and chr17q24 loci were selected for further investigation. We detected replicating association to low frequency variants in the TNFAIP3 gene (combined p = 6.6 × 10−6). Even though rare variants are not well-represented and can be difficult to genotype in GWAS, our study supports the application of low frequency variant collapsing methods to genome-wide SNP datasets as a means of exploiting data that are routinely ignored.
Electronic supplementary material
The online version of this article (doi:10.1007/s00439-010-0889-1) contains supplementary material, which is available to authorized users.
Linkage of the chromosome 1q21–25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23-Mb interval in a multiethnic sample to search for variants responsible for this linkage signal.
RESEARCH DESIGN AND METHODS
In all, 5,290 single nucleotide polymorphisms (SNPs) were successfully genotyped in 3,179 type 2 diabetes case and control subjects from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q linkage. After imputation, we estimate ∼80% coverage of common variation across the region (r 2 > 0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in ∼8,500 case subjects and 12,400 control subjects.
Association mapping of the 23-Mb region identified two strong signals, both of which were restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, odds ratio 1.38 [95% CI 1.21–1.57], P = 1.4 × 10−6, in 999 case subjects and 1,190 control subjects); the second mapped within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, odds ratio 1.48 [1.18–1.76], P = 1.0 × 10−5, under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), there was no indication that these variants were causally related to type 2 diabetes status.
Detailed fine-mapping of the 23-Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.
Genome-wide association studies have found type 2 diabetes-associated variants in the HNF1B gene to exhibit reciprocal associations with prostate cancer risk. We aimed to identify whether these variants may have an effect on cancer risk in general versus a specific effect on prostate cancer only.
In a collaborative analysis, we collected data from GWAS of cancer phenotypes for the frequently reported variants of HNF1B, rs4430796 and rs7501939, which are in linkage disequilibrium (r2 = 0.76, HapMap CEU). Overall, the analysis included 16 datasets on rs4430796 with 19,640 cancer cases and 21,929 controls; and 21 datasets on rs7501939 with 26,923 cases and 49,085 controls. Malignancies other than prostate cancer included colorectal, breast, lung and pancreatic cancers, and melanoma. Meta-analysis showed large between-dataset heterogeneity that was driven by different effects in prostate cancer and other cancers. The per-T2D-risk-allele odds ratios (95% confidence intervals) for rs4430796 were 0.79 (0.76, 0.83)] per G allele for prostate cancer (p<10−15 for both); and 1.03 (0.99, 1.07) for all other cancers. Similarly for rs7501939 the per-T2D-risk-allele odds ratios (95% confidence intervals) were 0.80 (0.77, 0.83) per T allele for prostate cancer (p<10−15 for both); and 1.00 (0.97, 1.04) for all other cancers. No malignancy other than prostate cancer had a nominally statistically significant association.
The examined HNF1B variants have a highly specific effect on prostate cancer risk with no apparent association with any of the other studied cancer types.
Linkage of the chromosome 1q21-25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23Mb interval in a multiethnic sample to search for variants responsible for this linkage signal.
Research Design and Methods
In all, 5,290 SNPs were successfully genotyped in 3,179 T2D cases and controls from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q-linkage. Following imputation, we estimate ~80% coverage of common variation across the region (r2>0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in approximately 8,500 cases and 12,400 controls.
Association mapping of the 23Mb region identified two strong signals, both restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, OR 1.38 (95% CI, 1.21-1.57), p=1.4×10-6 in 999 cases and 1,190 controls): the second within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, OR 1.48 [1.18-1.76], p=1.0×10-5, under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), no indication that these variants were causally-related to T2D status.
Detailed fine-mapping of the 23Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.
chromosome 1q; linkage; association
Genome-wide association (GWA) studies have identified multiple new genomic loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D)1-11. Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to discover loci at which common alleles have modest effects, we performed meta-analysis of three T2D GWA scans encompassing 10,128 individuals of European-descent and ~2.2 million SNPs (directly genotyped and imputed). Replication testing was performed in an independent sample with an effective sample size of up to 53,975. At least six new loci with robust evidence for association were detected, including the JAZF1 (p=5.0×10−14), CDC123/CAMK1D (p=1.2×10−10), TSPAN8/LGR5 (p=1.1×10−9), THADA (p=1.1×10−9), ADAMTS9 (p=1.2×10−8), and NOTCH2 (p=4.1×10−8) gene regions. The large number of loci with relatively small effects indicates the value of large discovery and follow-up samples in identifying additional clues about the inherited basis of T2D.
To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 × 10−6) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 × 10−15) and 5,988 children aged 7–11 (0.13 Z-score units; P = 1.5 × 10−8). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 × 10−11). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 × 10−4). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.
Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.
To evaluate the impact of a laboratory course on the manual blood pressure (BP) and heart rate (HR) measurement skills of pharmacy students.
After 1 lecture and 1 laboratory session on vital sign technique, pharmacy students enrolled in a patient assessment laboratory course were randomly paired with a classmate and manually measured the classmate's BP and HR. Within 2 minutes, the BP and HR were measured by an Omron 711-AC automatic monitor. The same assessment procedures with manual and automatic measurements were repeated near the end of the laboratory course. Student skills were also evaluated through direct observation by faculty members.
Student and machine measurements of systolic blood pressure (SBP), diastolic blood pressure (DBP), and HR significantly correlated at the final assessment (r = 0.92, 0.83, and 0.91 respectively; p < 0.001 for each. The proportion of student and device values agreeing to within 5 units (mmHg and beats-per-minute) at baseline versus at the final assessment significantly improved from 38% to 67% for SBP, 51% to 77% for DBP, and 52% to 79% for HR (p < 0.001 for each). The percentage of students correctly performing all 13 AHA endorsed steps for BP measurement improved significantly from 4.6% to 75.6% (p < 0.001).
Significant improvement and the attainment of competency in manual vital signs measurement were demonstrated by pharmacy students after 11 weeks of skill rehearsal in a laboratory course.
vital signs; blood pressure; heart rate; physical assessment; pharmacy students
Bin1 is a Myc-interacting protein with features of a tumor suppressor. The high level of Bin1 expression in skeletal muscle prompted us to investigate its role in muscle differentiation. Significant levels of Bin1 were observed in undifferentiated C2C12 myoblasts, a murine in vitro model system. Induction of differentiation by growth factor withdrawal led to an upregulation of Bin1 mRNA and to the generation of higher-molecular-weight forms of Bin1 protein by alternate splicing. While Bin1 in undifferentiated cells was localized exclusively in the nucleus, differentiation-associated isoforms of Bin1 were found in the cytoplasm as well. To examine the function of Bin1 during differentiation, we generated stable cell lines that express exogenous human Bin1 cDNA in the sense or antisense orientation. Cells overexpressing Bin1 grew more slowly than control cells and differentiated more rapidly when deprived of growth factors. In contrast, C2C12 cells expressing antisense Bin1 showed an impaired ability to undergo differentiation. Taken together, the results indicated that Bin1 expression, structure, and localization are tightly regulated during muscle differentiation and suggested that Bin1 plays a functional role in the differentiation process.
Obesity as measured by body mass index (BMI) is one of the major risk factors for osteoarthritis. In addition, genetic overlap has been reported between osteoarthritis and normal adult height variation. We investigated whether this relationship is due to a shared genetic aetiology on a genome-wide scale.
We compared genetic association summary statistics (effect size, p value) for BMI and height from the GIANT consortium genome-wide association study (GWAS) with genetic association summary statistics from the arcOGEN consortium osteoarthritis GWAS. Significance was evaluated by permutation. Replication of osteoarthritis association of the highlighted signals was investigated in an independent dataset. Phenotypic information of height and BMI was accounted for in a separate analysis using osteoarthritis-free controls.
We found significant overlap between osteoarthritis and height (p=3.3×10−5 for signals with p≤0.05) when the GIANT and arcOGEN GWAS were compared. For signals with p≤0.001 we found 17 shared signals between osteoarthritis and height and four between osteoarthritis and BMI. However, only one of the height or BMI signals that had shown evidence of association with osteoarthritis in the arcOGEN GWAS was also associated with osteoarthritis in the independent dataset: rs12149832, within the FTO gene (combined p=2.3×10−5). As expected, this signal was attenuated when we adjusted for BMI.
We found a significant excess of shared signals between both osteoarthritis and height and osteoarthritis and BMI, suggestive of a common genetic aetiology. However, only one signal showed association with osteoarthritis when followed up in a new dataset.
Osteoarthritis; Gene Polymorphism; Epidemiology