Common genetic variants and modification of penetrance of BRCA2-associated breast cancer

The considerable uncertainty regarding cancer risks associated with inherited mutations of BRCA2 is due to unknown factors. To investigate whether common genetic variants modify penetrance for BRCA2 mutation carriers, we undertook a two-staged genome-wide association study in BRCA2 mutation carriers. In stage 1 using the Affymetrix 6.0 platform, 592,163 filtered SNPs genotyped were available on 899 young (<40 years) affected and 804 unaffected carriers of European ancestry. Associations were evaluated using a survival-based score test adjusted for familial correlations and stratified by country of the study and BRCA2*6174delT mutation status. The genomic inflation factor (λ) was 1.011. The stage 1 association analysis revealed multiple variants associated with breast cancer risk: 3 SNPs had p-values<10(-5) and 39 SNPs had p-values<10(-4). These variants included several previously associated with sporadic breast cancer risk and two novel loci on chromosome 20 (rs311499) and chromosome 10 (rs16917302). The chromosome 10 locus was in ZNF365, which contains another variant that has recently been associated with breast cancer in an independent study of unselected cases. In stage 2, the top 85 loci from stage 1 were genotyped in 1,264 cases and 1,222 controls. Hazard ratios (HR) and 95% confidence intervals (CI) for stage 1 and 2 were combined and estimated using a retrospective likelihood approach, stratified by country of residence and the most common mutation, BRCA2*6174delT. The combined per allele HR of the minor allele for the novel loci rs16917302 was 0.75 (95% CI 0.66-0.86, ) and for rs311499 was 0.72 (95% CI 0.61-0.85, ). FGFR2 rs2981575 had the strongest association with breast cancer risk (per allele HR = 1.28, 95% CI 1.18-1.39, ). These results indicate that SNPs that modify BRCA2 penetrance identified by an agnostic approach thus far are limited to variants that also modify risk of sporadic BRCA2 wild-type breast cancer.     

Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer

Genome-wide association studies (GWAS) have identified 14 tagging single nucleotide polymorphisms (tagSNPs) that are associated with the risk of colorectal cancer (CRC), and several of these tagSNPs are near bone morphogenetic protein (BMP) pathway loci. The penalty of multiple testing implicit in GWAS increases the attraction of complementary approaches for disease gene discovery, including candidate gene- or pathway-based analyses. The strongest candidate loci for additional predisposition SNPs are arguably those already known both to have functional relevance and to be involved in disease risk. To investigate this proposition, we searched for novel CRC susceptibility variants close to the BMP pathway genes GREM1 (15q13.3), BMP4 (14q22.2), and BMP2 (20p12.3) using sample sets totalling 24,910 CRC cases and 26,275 controls. We identified new, independent CRC predisposition SNPs close to BMP4 (rs1957636, P = 3.93×10(-10)) and BMP2 (rs4813802, P = 4.65×10(-11)). Near GREM1, we found using fine-mapping that the previously-identified association between tagSNP rs4779584 and CRC actually resulted from two independent signals represented by rs16969681 (P = 5.33×10(-8)) and rs11632715 (P = 2.30×10(-10)). As low-penetrance predisposition variants become harder to identify-owing to small effect sizes and/or low risk allele frequencies-approaches based on informed candidate gene selection may become increasingly attractive. Our data emphasise that genetic fine-mapping studies can deconvolute associations that have arisen owing to independent correlation of a tagSNP with more than one functional SNP, thus explaining some of the apparently missing heritability of common diseases.     

Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients

Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury.Design Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: “basic” model (demographic and clinical variables only) and “CT” model (basic model plus results of computed tomography). The models were subsequently developed for high and low-middle income countries separately. Setting Medical Research Council (MRC) CRASH Trial.Subjects 10 008 patients with traumatic brain injury. Models externally validated in a cohort of 8509.Results The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer-Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration.Conclusion Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.     

A New Statistic to Evaluate Imputation Reliability

Background

As the amount of data from genome wide association studies grows dramatically, many interesting scientific questions require imputation to combine or expand datasets. However, there are two situations for which imputation has been problematic: (1) polymorphisms with low minor allele frequency (MAF), and (2) datasets where subjects are genotyped on different platforms. Traditional measures of imputation cannot effectively address these problems.

Methodology/Principal Findings

We introduce a new statistic, the imputation quality score (IQS). In order to differentiate between well-imputed and poorly-imputed single nucleotide polymorphisms (SNPs), IQS adjusts the concordance between imputed and genotyped SNPs for chance. We first evaluated IQS in relation to minor allele frequency. Using a sample of subjects genotyped on the Illumina 1 M array, we extracted those SNPs that were also on the Illumina 550 K array and imputed them to the full set of the 1 M SNPs. As expected, the average IQS value drops dramatically with a decrease in minor allele frequency, indicating that IQS appropriately adjusts for minor allele frequency. We then evaluated whether IQS can filter poorly-imputed SNPs in situations where cases and controls are genotyped on different platforms. Randomly dividing the data into “cases” and “controls”, we extracted the Illumina 550 K SNPs from the cases and imputed the remaining Illumina 1 M SNPs. The initial Q-Q plot for the test of association between cases and controls was grossly distorted (λ = 1.15) and had 4016 false positives, reflecting imputation error. After filtering out SNPs with IQS<0.9, the Q-Q plot was acceptable and there were no longer false positives. We then evaluated the robustness of IQS computed independently on the two halves of the data. In both European Americans and African Americans the correlation was >0.99 demonstrating that a database of IQS values from common imputations could be used as an effective filter to combine data genotyped on different platforms.

Conclusions/Significance

IQS effectively differentiates well-imputed and poorly-imputed SNPs. It is particularly useful for SNPs with low minor allele frequency and when datasets are genotyped on different platforms.     

Lymphotoxin-alpha gene and risk of myocardial infarction in 6,928 cases and 2,712 controls in the ISIS case-control study

Lymphotoxin-alpha (LTA) is a pro-inflammatory cytokine that plays an important role in the immune system and local inflammatory response. LTA is expressed in atherosclerotic plaques and has been implicated in the pathogenesis of atherosclerosis and coronary heart disease (CHD). Polymorphisms in the gene encoding lymphotoxin-alpha (LTA) on Chromosome 6p21 have been associated with susceptibility to CHD, but results in different studies appear to be conflicting. We examined the association of seven single nucleotide polymorphisms (SNPs) across the LTA gene, and their related haplotypes, with risk of myocardial infarction (MI) in the International Study of Infarct Survival (ISIS) case-control study involving 6,928 non-fatal MI cases and 2,712 unrelated controls. The seven SNPs (including the rs909253 and rs1041981 SNPs previously implicated in the risk of CHD) were in strong linkage disequilibrium with each other and contributed to six common haplotypes. Some of the haplotypes for LTA were associated with higher plasma concentrations of C-reactive protein (p = 0.004) and lower concentrations of albumin (p = 0.023). However, none of the SNPs or related haplotypes were significantly associated with risk of MI. The results of the ISIS study were considered in the context of six previously published studies that had assessed this association, and this meta-analysis found no significant association with CHD risk using a recessive model and only a modest association using a dominant model (with narrow confidence intervals around these risk estimates). Overall, these studies provide reliable evidence that these common polymorphisms for the LTA gene are not strongly associated with susceptibility to coronary disease.     

Snakebite mortality in India: a nationally representative mortality survey

Background

India has long been thought to have more snakebites than any other country. However, inadequate hospital-based reporting has resulted in estimates of total annual snakebite mortality ranging widely from about 1,300 to 50,000. We calculated direct estimates of snakebite mortality from a national mortality survey.

Methods and Findings

We conducted a nationally representative study of 123,000 deaths from 6,671 randomly selected areas in 2001–03. Full-time, non-medical field workers interviewed living respondents about all deaths. The underlying causes were independently coded by two of 130 trained physicians. Discrepancies were resolved by anonymous reconciliation or, failing that, by adjudication.A total of 562 deaths (0.47% of total deaths) were assigned to snakebites. Snakebite deaths occurred mostly in rural areas (97%), were more common in males (59%) than females (41%), and peaked at ages 15–29 years (25%) and during the monsoon months of June to September. This proportion represents about 45,900 annual snakebite deaths nationally (99% CI 40,900 to 50,900) or an annual age-standardised rate of 4.1/100,000 (99% CI 3.6–4.5), with higher rates in rural areas (5.4/100,000; 99% CI 4.8–6.0), and with the highest state rate in Andhra Pradesh (6.2). Annual snakebite deaths were greatest in the states of Uttar Pradesh (8,700), Andhra Pradesh (5,200), and Bihar (4,500).

Conclusions

Snakebite remains an underestimated cause of accidental death in modern India. Because a large proportion of global totals of snakebites arise from India, global snakebite totals might also be underestimated. Community education, appropriate training of medical staff and better distribution of antivenom, especially to the 13 states with the highest prevalence, could reduce snakebite deaths in India.     

Deaths from Symptomatically Identifiable Furious Rabies in India: A Nationally Representative Mortality Survey

Background

It is estimated that India has more deaths from rabies than any other country. However, existing estimates are indirect and rely on non-representative studies.

Methods and Principal Findings

We examined rabies deaths in the ongoing Million Death Study (MDS), a representative survey of over 122,000 deaths in India that uses enhanced types of verbal autopsy. We estimated the age-specific mortality rates of symptomatically identifiable furious rabies and its geographic and demographic distributions. A total of 140 deaths in our sample were caused by rabies, suggesting that in 2005 there were 12,700 (99% CI 10,000 to 15,500) symptomatically identifiable furious rabies deaths in India. Most rabies deaths were in males (62%), in rural areas (91%), and in children below the age of 15 years (50%). The overall rabies mortality rate was 1.1 deaths per 100,000 population (99%CI 0.9 to 1.4). One third of the national rabies deaths were found in Uttar Pradesh (4,300) and nearly three quarters (8,900) were in 7 central and south-eastern states: Chhattisgarh, Uttar Pradesh, Odisha, Andhra Pradesh, Bihar, Assam, and Madhya Pradesh.

Conclusions and Significance

Rabies remains an avoidable cause of death in India. As verbal autopsy is not likely to identify atypical or paralytic forms of rabies, our figure of 12,700 deaths due to classic and clinically identifiable furious rabies underestimates the total number of deaths due to this virus. The concentrated geographic distribution of rabies in India suggests that a significant reduction in the number of deaths or potentially even elimination of rabies deaths is possible.