A dataset of proteomic changes during human heat stress and heat acclimation

Hotter climates have important impacts on human health and performance. Yet, the cellular and molecular responses involved in human heat stress and acclimation remain understudied. This dataset includes physiological measurements and the plasma concentration of 2,938 proteins collected from 10 healthy adults, before and during passive heat stress that was performed both prior to and after a 7-day heat acclimation protocol. Physiological measurements included body temperatures, sweat rate, cutaneous vascular conductance, blood pressure, and skin sympathetic nerve activity. The proteomic dataset was generated using the Olink Explore 3072 assay, enabling a high-multiplex antibody-based assessment of protein changes based on proximity extension assay technology. The data need to be interpreted in the context of the moderate level of body hyperthermia attained and the specific demographic of young, healthy adults. We have made this dataset publicly available to facilitate research into the cellular and molecular mechanisms involved in human heat stress and acclimation, crucial for addressing the health and performance challenges posed by rising temperatures.

Pharmacogenomic markers of metoprolol and α-OH-metoprolol concentrations: a genome-wide association study

Aim: Few genome-wide association studies (GWASs) have been conducted to identify predictors of drug concentrations. The authors therefore sought to discover the pharmacogenomic markers involved in metoprolol pharmacokinetics. Patients & methods: The authors performed a GWAS of a cross-sectional study of 993 patients from the Montreal Heart Institute Biobank taking metoprolol. Results: A total of 391 and 444 SNPs reached the significance threshold of 5 × 10-8 for metoprolol and α-OH-metoprolol concentrations, respectively. All were located on chromosome 22 at or near the CYP2D6 gene, encoding CYP450 2D6, metoprolol's main metabolizing enzyme. Conclusion: The results reinforce previous findings of the importance of the CYP2D6 locus for metoprolol concentrations and confirm that large biobanks can be used to identify genetic determinants of drug pharmacokinetics at a GWAS significance level.

Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors

BACKGROUND

Cancer survivors are at an increased risk of cardiovascular disease (CVD) compared to the general population. We sought to evaluate the impact of mosaic chromosomal alterations (mCAs) on death of CVD causes, coronary artery disease (CAD) causes, and of any cause in patients with a cancer diagnosis.

METHODS

The study was a prospective cohort analysis of 48,919 UK Biobank participants with a cancer diagnosis. mCAs were characterized using DNA genotyping array intensity data and long-range chromosomal phase inference. Multivariable Cox regression models were used to ascertain the associations of mCAs. Exploratory endpoints included various incident cardiovascular phenotypes.

RESULTS

Overall, 10,070 individuals (20.6%) carried ≥1 mCA clone. In adjusted analyses, mCA was associated with an increased risk of death of CAD causes (HR: 1.37, 95% CI: 1.09-1.71, P=0.006). In sub-analyses, we found that carriers of mCAs diagnosed with kidney cancer had an increased risk of death of CVD causes (HR: 2.03, 95% CI: 1.11-3.72, P=0.022) and CAD causes (HR: 3.57, 95% CI: 1.44-8.84, P=0.006). Women diagnosed with breast cancer who carried a mCA also had a higher risk of death of CAD causes (HR: 2.46, 95% CI: 1.23-4.92, P=0.011).

CONCLUSIONS

Among cancer survivors, carriers of any mCA are at an increased risk of CAD death compared to non-carriers. Mechanistic studies should be considered to better ascertain the biological mechanisms underneath the observed associations between mCAs and cardiovascular events for specific cancer types.

IMPACT

There may be clinical relevance in considering mCAs in patients diagnosed with cancer and undergoing treatment.

Study of effect modifiers of genetically predicted CETP reduction

Genetic variants in drug targets can be used to predict the long-term, on-target effect of drugs. Here, we extend this principle to assess how sex and body mass index may modify the effect of genetically predicted lower CETP levels on biomarkers and cardiovascular outcomes. We found sex and body mass index (BMI) to be modifiers of the association between genetically predicted lower CETP and lipid biomarkers in UK Biobank participants. Female sex and lower BMI were associated with higher high-density lipoprotein cholesterol and lower low-density lipoprotein cholesterol for the same genetically predicted reduction in CETP concentration. We found that sex also modulated the effect of genetically lower CETP on cholesterol efflux capacity in samples from the Montreal Heart Institute Biobank. However, these modifying effects did not extend to sex differences in cardiovascular outcomes in our data. Our results provide insight into the clinical effects of CETP inhibitors in the presence of effect modification based on genetic data. The approach can support precision medicine applications and help assess the external validity of clinical trials.

Do variants in the coding regions of FOXP2, a gene implicated in speech disorder, confer a risk for congenital amusia?

Congenital amusia is a lifelong disorder that compromises the normal development of musical abilities in 1.5-4% of the general population. There is a substantial genetic contribution to congenital amusia, and it bears similarities to neurodevelopmental disorders of language. Here, we examine the extent to which variants in the forkhead box P2 gene (FOXP2)-the first gene to be identified as causal in developmental speech deficits-are associated with the amusic trait. Using a cohort of 49 individuals with amusia, of which 27 were unrelated, the role of FOXP2 variants in amusia was evaluated. Fourteen variants were examined in the cohort. None segregated with the amusic trait among participants for whom family information was available; nor were they predicted to be deleterious to protein function. Thus, variants in FOXP2 are not likely to cause amusia. Implications for ongoing debates about the distinction between musicality and language are discussed.

ExPheWas: a platform for cis-Mendelian randomization and gene-based association scans

Establishing the relationship between protein-coding genes and phenotypes has the potential to inform on the molecular etiology of diseases. Here, we describe ExPheWas (exphewas.ca), a gene-based phenome-wide association study browser and platform that enables the conduct of gene-based Mendelian randomization. The ExPheWas data repository includes sex-stratified and sex-combined gene-based association results from 26 616 genes with 1746 phenotypes measured in up to 413 133 individuals from the UK Biobank. Interactive visualizations are provided through a browser to facilitate data exploration supported by false discovery rate control, and it includes tools for enrichment analysis. The interactive Mendelian randomization module in ExPheWas allows the estimation of causal effects of a genetically predicted exposure on an outcome by using genetic variation in a single gene as the instrumental variable.

Construction of a femininity score in the UK Biobank and its association with angina diagnosis prior to myocardial infarction

Gender captures social components beyond biological sex and can add valuable insight to health studies in populations. However, assessment of gender typically relies on questionnaires which may not be available. The aim of this study is to construct a gender metric using available variables in the UK Biobank and to apply it to the study of angina diagnosis. Proxy variables for femininity characteristics were identified in the UK Biobank and regressed on sex to construct a composite femininity score (FS) validated using tenfold cross-validation. The FS was assessed as a predictor of angina diagnosis before incident myocardial infarction (MI) events. The FS was derived for 315,937 UK Biobank participants. In 3059 individuals with no history of MI at study entry who had an incident MI event, the FS was a significant predictor of angina diagnosis prior to MI (OR 1.24, 95% CI 1.10-1.39, P < 0.001) with a significant sex-by-FS interaction effect (P = 0.003). The FS was positively associated with angina diagnosis prior to MI in men (OR 1.37, 95% CI 1.19-1.57, P < 0.001), but not in women. We have provided a new tool to conduct gender-sensitive analyses in observational studies, and applied it to study of angina diagnosis prior to MI.

The genomics of heart failure: design and rationale of the HERMES consortium

Aims

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure.

Methods and results

The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome‐wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow‐up following heart failure diagnosis ranged from 2 to 116 months. Forty‐nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low‐frequency variants (allele frequency 0.01–0.05) at P < 5 × 10⁻⁸ under an additive genetic model.

Conclusions

HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Genetics of symptom remission in outpatients with COVID-19

We conducted a genome-wide association study of time to remission of COVID-19 symptoms in 1723 outpatients with at least one risk factor for disease severity from the COLCORONA clinical trial. We found a significant association at 5p13.3 (rs1173773; P = 4.94 × 10^-8) near the natriuretic peptide receptor 3 gene (NPR3). By day 15 of the study, 44%, 54% and 59% of participants with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. In 851 participants not treated with colchicine (placebo), there was a significant association at 9q33.1 (rs62575331; P = 2.95 × 10^-8) in interaction with colchicine (P = 1.19 × 10^-5) without impact on risk of hospitalisations, highlighting a possibly shared mechanistic pathway. By day 15 of the study, 46%, 62% and 64% of those with 0, 1, or 2 copies of the effect allele respectively, had symptom remission. The findings need to be replicated and could contribute to the biological understanding of COVID-19 symptom remission.

Pharmacogenomics of the Efficacy and Safety of Colchicine in COLCOT

Supplemental Digital Content is available in the text.

Background:

The randomized, placebo-controlled COLCOT (Colchicine Cardiovascular Outcomes Trial) has shown the benefits of colchicine 0.5 mg daily to lower the rate of ischemic cardiovascular events in patients with a recent myocardial infarction. Here, we conducted a post hoc pharmacogenomic study of COLCOT with the aim to identify genetic predictors of the efficacy and safety of treatment with colchicine.

Methods:

There were 1522 participants of European ancestry from the COLCOT trial available for the pharmacogenomic study of COLCOT trial. The pharmacogenomic study’s primary cardiovascular end point was defined as for the main trial, as time to first occurrence of cardiovascular death, resuscitated cardiac arrest, myocardial infarction, stroke, or urgent hospitalization for angina requiring coronary revascularization. The safety end point was time to the first report of gastrointestinal events. Patients’ DNA was genotyped using the Illumina Global Screening array followed by imputation. We performed a genome-wide association study in colchicine-treated patients.

Results:

None of the genetic variants passed the genome-wide association study significance threshold for the primary cardiovascular end point conducted in 702 patients in the colchicine arm who were compliant to medication. The genome-wide association study for gastrointestinal events was conducted in all 767 patients in the colchicine arm and found 2 significant association signals, one with lead variant rs6916345 (hazard ratio, 1.89 [95% CI, 1.52–2.35], P=7.41×10⁻⁹) in a locus which colocalizes with Crohn disease, and one with lead variant rs74795203 (hazard ratio, 2.51 [95% CI, 1.82–3.47]; P=2.70×10⁻⁸), an intronic variant in gene SEPHS1. The interaction terms between the genetic variants and treatment with colchicine versus placebo were significant.

Conclusions:

We found 2 genomic regions associated with gastrointestinal events in patients treated with colchicine. Those findings will benefit from replication to confirm that some patients may have genetic predispositions to lower tolerability of treatment with colchicine.

A genetic model of ivabradine recapitulates results from randomized clinical trials

BACKGROUND

Naturally occurring human genetic variants provide a valuable tool to identify drug targets and guide drug prioritization and clinical trial design. Ivabradine is a heart rate lowering drug with protective effects on heart failure despite increasing the risk of atrial fibrillation. In patients with coronary artery disease without heart failure, the drug does not protect against major cardiovascular adverse events prompting questions about the ability of genetics to have predicted those effects. This study evaluates the effect of a variant in HCN4, ivabradine's drug target, on safety and efficacy endpoints.

METHODS

We used genetic association testing and Mendelian randomization to predict the effect of ivabradine and heart rate lowering on cardiovascular outcomes.

RESULTS

Using data from the UK Biobank and large GWAS consortia, we evaluated the effect of a heart rate-reducing genetic variant at the HCN4 locus encoding ivabradine's drug target. These genetic association analyses showed increases in risk for atrial fibrillation (OR 1.09, 95% CI: 1.06-1.13, P = 9.3 ×10-9) in the UK Biobank. In a cause-specific competing risk model to account for the increased risk of atrial fibrillation, the HCN4 variant reduced incident heart failure in participants that did not develop atrial fibrillation (HR 0.90, 95% CI: 0.83-0.98, P = 0.013). In contrast, the same heart rate reducing HCN4 variant did not prevent a composite endpoint of myocardial infarction or cardiovascular death (OR 0.99, 95% CI: 0.93-1.04, P = 0.61).

CONCLUSION

Genetic modelling of ivabradine recapitulates its benefits in heart failure, promotion of atrial fibrillation, and neutral effect on myocardial infarction.

Pharmacogenetic content of commercial genome-wide genotyping arrays

Aim: We have evaluated the pharmacogenetic content of commercial human genome-wide genotyping arrays, as it is a critical determinant to enabling pharmacogenomic discoveries. Methods: Using bioinformatics approaches, we assessed 27,811 genetic variants in 3146 genes for their presence in 18 Illumina and 15 Affymetrix genome-wide arrays. Results: The pharmacogenetic content of the arrays varied greatly. The combination of the Affymetrix precision medicine array and PharmacoScan arrays (Affymetrix) had the highest coverage for a set of clinically actionable absorption, distribution, metabolism and excretion (ADME) variants, single nucleotide ADME variants and ADME insertions/deletions, with a physical coverage of 125/130 (96.2%), 9924/24,138 (41.1%) and 2252/3994 (56.4%), respectively. Conclusion: The combination of the Affymetrix precision medicine array and PharmacoScan arrays provided both genome-wide and pharmacogene coverage, which is crucial in the discovering of new variants responsible for drug adverse effects. These results will help in the design of pharmacogenomic studies and will enable a critical review of results from past studies.

Methylomic changes in individuals with psychosis, prenatally exposed to endocrine disrupting compounds: Lessons from diethylstilbestrol

BACKGROUND

In the Western world, between 1940 and 1970, more than 2 million people were exposed in utero to diethylstilbestrol (DES). In exposed individuals, and in their descendants, adverse outcomes have been linked to such exposure, including cancers, genital malformations, and less consistently, psychiatric disorders. We aimed to explore whether prenatal DES exposure would be associated with DNA methylation changes, and whether these epigenetic modifications would be associated with increased risk of psychosis.

METHODS

From 247 individuals born from mothers exposed to DES, we selected 69 siblings from 30 families. In each family, at least one sibling was exposed in utero to DES. We performed a methylome-wide association study using HumanMethylation450 DNA Analysis BeadChip® in peripheral blood. We analyzed methylation changes at individual CpGs or regions in exposed (n = 37) versus unexposed individuals (n = 32). We also compared exposed individuals with (n = 7) and without psychosis (n = 30).

RESULTS

There were more individuals with schizophrenia in the DES-exposed group. We found no significant differences between exposed and unexposed individuals with respect to differentially methylated CpGs or regions. The largest difference was in a region near the promoter of an ADAMTS proteoglycanase gene (ADAMTS9). Compared to exposed individuals without psychosis, exposed individuals with psychosis had differential methylation in the region encompassing the gene encoding the zinc finger protein 57 (ZFP57).

CONCLUSIONS

In utero exposure to DES was not associated with methylation changes at specific CpG or regions. In exposed individuals, however, psychosis was associated with specific methylomic modifications that could impact neurodevelopment and neuroplasticity.

genipe: an automated genome-wide imputation pipeline with automatic reporting and statistical tools

Summary: Genotype imputation is now commonly performed following genome-wide genotyping experiments. Imputation increases the density of analyzed genotypes in the dataset, enabling fine-mapping across the genome. However, the process of imputation using the most recent publicly available reference datasets can require considerable computation power and the management of hundreds of large intermediate files. We have developed genipe, a complete genome-wide imputation pipeline which includes automatic reporting, imputed data indexing and management, and a suite of statistical tests for imputed data commonly used in genetic epidemiology (Sequence Kernel Association Test, Cox proportional hazards for survival analysis, and linear mixed models for repeated measurements in longitudinal studies).

Availability and Implementation: The genipe package is an open source Python software and is freely available for non-commercial use (CC BY-NC 4.0) at https://github.com/pgxcentre/genipe. Documentation and tutorials are available at http://pgxcentre.github.io/genipe.

Contact:louis-philippe.lemieux.perreault@statgen.org or marie-pierre.dube@statgen.org

Supplementary information:Supplementary data are available at Bioinformatics online.

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease

BACKGROUND

The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets.

METHODS

Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes.

RESULTS

We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)).

CONCLUSIONS

We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Pharmacogenomic determinants of the cardiovascular effects of dalcetrapib

BACKGROUND

Dalcetrapib did not improve clinical outcomes, despite increasing high-density lipoprotein cholesterol by 30%. These results differ from other evidence supporting high-density lipoprotein as a therapeutic target. Responses to dalcetrapib may vary according to patients' genetic profile.

METHODS AND RESULTS

We conducted a pharmacogenomic evaluation using a genome-wide approach in the dal-OUTCOMES study (discovery cohort, n=5749) and a targeted genotyping panel in the dal-PLAQUE-2 imaging trial (support cohort, n=386). The primary endpoint for the discovery cohort was a composite of cardiovascular events. The change from baseline in carotid intima-media thickness on ultrasonography at 6 and 12 months was evaluated as supporting evidence. A single-nucleotide polymorphism was found to be associated with cardiovascular events in the dalcetrapib arm, identifying the ADCY9 gene on chromosome 16 (rs1967309; P=2.41×10(-8)), with 8 polymorphisms providing P<10(-6) in this gene. Considering patients with genotype AA at rs1967309, there was a 39% reduction in the composite cardiovascular endpoint with dalcetrapib compared with placebo (hazard ratio, 0.61; 95% confidence interval, 0.41-0.92). In patients with genotype GG, there was a 27% increase in events with dalcetrapib versus placebo. Ten single-nucleotide polymorphism in the ADCY9 gene, the majority in linkage disequilibrium with rs1967309, were associated with the effect of dalcetrapib on intima-media thickness (P<0.05). Marker rs2238448 in ADCY9, in linkage disequilibrium with rs1967309 (r(2)=0.8), was associated with both the effects of dalcetrapib on intima-media thickness in dal-PLAQUE-2 (P=0.009) and events in dal-OUTCOMES (P=8.88×10(-8); hazard ratio, 0.67; 95% confidence interval, 0.58-0.78).

CONCLUSIONS

The effects of dalcetrapib on atherosclerotic outcomes are determined by correlated polymorphisms in the ADCY9 gene.

CLINICAL TRIAL INFORMATION

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00658515 and NCT01059682.

An inherited duplication at the gene p21 Protein-Activated Kinase 7 (PAK7) is a risk factor for psychosis

Identifying rare, highly penetrant risk mutations may be an important step in dissecting the molecular etiology of schizophrenia. We conducted a gene-based analysis of large (>100 kb), rare copy-number variants (CNVs) in the Wellcome Trust Case Control Consortium 2 (WTCCC2) schizophrenia sample of 1564 cases and 1748 controls all from Ireland, and further extended the analysis to include an additional 5196 UK controls. We found association with duplications at chr20p12.2 (P = 0.007) and evidence of replication in large independent European schizophrenia (P = 0.052) and UK bipolar disorder case-control cohorts (P = 0.047). A combined analysis of Irish/UK subjects including additional psychosis cases (schizophrenia and bipolar disorder) identified 22 carriers in 11 707 cases and 10 carriers in 21 204 controls [meta-analysis Cochran-Mantel-Haenszel P-value = 2 × 10(-4); odds ratio (OR) = 11.3, 95% CI = 3.7, ∞]. Nineteen of the 22 cases and 8 of the 10 controls carried duplications starting at 9.68 Mb with similar breakpoints across samples. By haplotype analysis and sequencing, we identified a tandem ~149 kb duplication overlapping the gene p21 Protein-Activated Kinase 7 (PAK7, also called PAK5) which was in linkage disequilibrium with local haplotypes (P = 2.5 × 10(-21)), indicative of a single ancestral duplication event. We confirmed the breakpoints in 8/8 carriers tested and found co-segregation of the duplication with illness in two additional family members of one of the affected probands. We demonstrate that PAK7 is developmentally co-expressed with another known psychosis risk gene (DISC1) suggesting a potential molecular mechanism involving aberrant synapse development and plasticity.

Comparison of genotype clustering tools with rare variants

Background

Along with the improvement of high throughput sequencing technologies, the genetics community is showing marked interest for the rare variants/common diseases hypothesis. While sequencing can still be prohibitive for large studies, commercially available genotyping arrays targeting rare variants prove to be a reasonable alternative. A technical challenge of array based methods is the task of deriving genotype classes (homozygous or heterozygous) by clustering intensity data points. The performance of clustering tools for common polymorphisms is well established, while their performance when conducted with a large proportion of rare variants (where data points are sparse for genotypes containing the rare allele) is less known. We have compared the performance of four clustering tools (GenCall, GenoSNP, optiCall and zCall) for the genotyping of over 10,000 samples using the Illumina’s HumanExome BeadChip, which includes 247,870 variants, 90% of which have a minor allele frequency below 5% in a population of European ancestry. Different reference parameters for GenCall and different initial parameters for GenoSNP were tested. Genotyping accuracy was assessed using data from the 1000 Genomes Project as a gold standard, and agreement between tools was measured.

Results

Concordance of GenoSNP’s calls with the gold standard was below expectations and was increased by changing the tool’s initial parameters. While the four tools provided concordance with the gold standard above 99% for common alleles, some of them performed poorly for rare alleles. The reproducibility of genotype calls for each tool was assessed using experimental duplicates which provided concordance rates above 99%. The inter-tool agreement of genotype calls was high for approximately 95% of variants. Most tools yielded similar error rates (approximately 0.02), except for zCall which performed better with a 0.00164 mean error rate.

Conclusions

The GenoSNP clustering tool could not be run straight “out of the box” with the HumanExome BeadChip, as modification of hard coded parameters was necessary to achieve optimal performance. Overall, GenCall marginally outperformed the other tools for the HumanExome BeadChip. The use of experimental replicates provided a valuable quality control tool for genotyping projects with rare variants.

pyGenClean: efficient tool for genetic data clean up before association testing

Summary: Genetic association studies making use of high-throughput genotyping arrays need to process large amounts of data in the order of millions of markers per experiment. The first step of any analysis with genotyping arrays is typically the conduct of a thorough data clean up and quality control to remove poor quality genotypes and generate metrics to inform and select individuals for downstream statistical analysis. We have developed pyGenClean, a bioinformatics tool to facilitate and standardize the genetic data clean up pipeline with genotyping array data. In conjunction with a source batch-queuing system, the tool minimizes data manipulation errors, accelerates the completion of the data clean up process and provides informative plots and metrics to guide decision making for statistical analysis.

Availability and implementation:pyGenClean is an open source Python 2.7 software and is freely available, along with documentation and examples, from http://www.statgen.org.

Contact:louis-philippe.lemieux.perreault@umontreal.ca or marie-pierre.dube@statgen.org

Partitioning of copy-number genotypes in pedigrees

Background

Copy number variations (CNVs) and polymorphisms (CNPs) have only recently gained the genetic community's attention. Conservative estimates have shown that CNVs and CNPs might affect more than 10% of the genome and that they may be at least as important as single nucleotide polymorphisms in assessing human variability. Widely used tools for CNP analysis have been implemented in Birdsuite and PLINK for the purpose of conducting genetic association studies based on the unpartitioned total number of CNP copies provided by the intensities from Affymetrix's Genome-Wide Human SNP Array. Here, we are interested in partitioning copy number variations and polymorphisms in extended pedigrees for the purpose of linkage analysis on familial data.

Results

We have developed CNGen, a new software for the partitioning of copy number polymorphism using the integrated genotypes from Birdsuite with the Affymetrix platform. The algorithm applied to familial trios or extended pedigrees can produce partitioned copy number genotypes with distinct parental alleles. We have validated the algorithm using simulations on a complex pedigree structure using frequencies calculated from a real dataset of 300 genotyped samples from 42 pedigrees segregating a congenital heart defect phenotype.

Conclusions

CNGen is the first published software for the partitioning of copy number genotypes in pedigrees, making possible the use CNPs and CNVs for linkage analysis. It was implemented with the Python interpreter version 2.5.2. It was successfully tested on current Linux, Windows and Mac OS workstations.