Comprehensive association analysis of speech recognition thresholds after cisplatin-based chemotherapy in survivors of adult-onset cancer.

PURPOSE: Deficits in speech understanding constitute one of the most severe consequences of hearing loss. Here we investigate the clinical and genetic risk factors for symmetric deterioration of speech recognition thresholds (SRT) among cancer survivors treated with cisplatin. METHODS: SRT was measured using spondaic words and calculating the mean of measurements for both ears with symmetric SRT values. For clinical associations, SRT-based hearing disability (SHD) was defined as SRT≥15 dB hearing loss and clinical variables were derived from the study dataset. Genotyped blood samples were used for GWAS with rank-based inverse normal transformed SRT values as the response variable. Age was used as a covariate in association analyses. RESULTS: SHD was inversely associated with self-reported health (p = 0.004). Current smoking (p = 0.002), years of smoking (p = 0.02), BMI (p < 0.001), and peripheral motor neuropathy (p = 0.003) were positively associated with SHD, while physical activity was inversely associated with SHD (p = 0.005). In contrast, cumulative cisplatin dose, peripheral sensory neuropathy, hypertension, and hypercholesterolemia were not associated with SHD. Although no genetic variants had an association p value < 5 × 10-8 , 22 genetic variants were suggestively associated (p < 10-5 ) with SRT deterioration. Three of the top variants in 10 respective linkage disequilibrium regions were either positioned within the coding sequence or were eQTLs for genes involved in neuronal development (ATE1, ENAH, and ZFHX3). CONCLUSION: Current results improve our understanding of risk factors for SRT deterioration in cancer survivors. Higher BMI, lower physical activity, and smoking are associated with SHD. Larger samples would allow for expansion of the current findings on the genetic architecture of SRT.

The Obstetrical Care and Delivery Experience of Women with Epilepsy in the MONEAD Study.

OBJECTIVE: We examined mode of delivery among pregnant women with epilepsy (PWWE) versus pregnant controls (PC). We hypothesize that PWWE are more likely to deliver by cesarean. STUDY DESIGN: The Maternal Outcomes and Neurodevelopmental Effects of Antiepileptic Drugs (MONEAD) study is an observational, prospective, multicenter investigation of pregnancy outcomes funded by the National Institute of Health (NIH). MONEAD enrolled patients from December 2012 through January 2016. PWWE were matched to PC in a case:control ratio of 3:1. This analysis had 80% power to detect a 36% increase in cesarean frequency assuming a baseline rate of 30% among PC at an α = 0.05. RESULTS: This report analyzed 331 PWWE (76%) and 102 PC (24%) who gave birth while enrolled in the study. PWWE and PC had similar rates of cesarean delivery (34.7 vs. 28.6%; p = 0.27). Of women with cesarean, rates of cesarean without labor were similar between groups for those delivering in recruitment hospitals (48.2 vs. 50.0%) but in nonrecruitment hospitals, cesarean rates without labor were over two-fold higher among PWWE than those of PC (68.8 vs. 30.8%; p = 0.023). Receipt of a cesarean after labor did not differ for PWWE compared to PC or by type of antiepileptic drug among the PWWE. CONCLUSION: These findings suggest that the obstetrical experiences of PWWE and PC are similar. An interesting deviation from this observation was the mode of delivery with higher unlabored cesarean rates occurring among PWWE in nonrecruitment hospitals. As the study recruitment hospitals were tertiary academic centers and nonrecruitment hospitals tended to be community-based institutions, differences in perinatal expertise might contribute to this difference. KEY POINTS: · Unlabored cesarean rates higher among women with epilepsy.. · Provider preference may influence delivery mode among women with epilepsy.. · Type and amount of antiepileptic drug was not associated with mode of delivery..

Changes in the Vaginal Microbiome and Associated Toxicities Following Radiation Therapy for Gynecologic Cancers.

Postmenopausal women often suffer from vaginal symptoms associated with atrophic vaginitis. Additionally, gynecologic cancer survivors may live for decades with additional, clinically significant, persistent vaginal toxicities caused by cancer therapies, including pain, dyspareunia, and sexual dysfunction. The vaginal microbiome (VM) has been previously linked with vaginal symptoms related to menopause (i.e. dryness). Our previous work showed that gynecologic cancer patients exhibit distinct VM profiles from healthy women, with low abundance of lactobacilli and prevalence of multiple opportunistic pathogenic bacteria. Here we explore the association between the dynamics and structure of the vaginal microbiome with the manifestation and persistence of vaginal symptoms, during one year after completion of cancer therapies, while controlling for clinical and sociodemographic factors. We compared cross-sectionally the vaginal microbiome in 134 women, 64 gynecologic patients treated with radiotherapy and 68 healthy controls, and we longitudinally followed a subset of 52 women quarterly (4 times in a year: pre-radiation therapy, 2, 6 and 12 months post-therapy). Differences among the VM profiles of cancer and healthy women were more pronounced with the progression of time. Cancer patients had higher diversity VMs and a variety of vaginal community types (CTs) that are not dominated by Lactobacilli, with extensive VM variation between individuals. Additionally, cancer patients exhibit highly unstable VMs (based on Bray-Curtis distances) compared to healthy controls. Vaginal symptoms prevalent in cancer patients included vaginal pain (40%), hemorrhage (35%), vaginismus (28%) and inflammation (20%), while symptoms such as dryness (45%), lack of lubrication (33%) and dyspareunia (32%) were equally or more prominent in healthy women at baseline. However, 24% of cancer patients experienced persistent symptoms at all time points, as opposed to 12% of healthy women. Symptom persistence was strongly inversely correlated with VM stability; for example, patients with persistent dryness or abnormally high pH have the most unstable microbiomes. Associations were identified between vaginal symptoms and individual bacterial taxa, including: Prevotella with vaginal dryness, Delftia with pain following vaginal intercourse, and Gemillaceaea with low levels of lubrication during intercourse. Taken together our results indicate that gynecologic cancer therapy is associated with reduced vaginal microbiome stability and vaginal symptom persistence.

Exploring the Vaginal Microbiome and Intravaginal Practices in Postmenopausal Women.

BACKGROUND: Evidence suggests that intravaginal practices (IVPs) women use to cleanse their vagina or enhance sexual pleasure may be associated with unhealthy changes in the vaginal microbiome (VM). However, the effects of these practices in postmenopausal women are unknown. OBJECTIVES: The objective of this pilot study was to characterize the VM communities of postmenopausal women, identify types and frequency of IVPs, and explore associations between the VM and IVPs in postmenopausal women. METHODS: We analyzed the VM data of 21 postmenopausal women in Atlanta, Georgia, from vaginal swabs collected at a routine gynecological visit. 16S rRNA gene sequencing in the V3-V4 region was used to characterize the VM. In addition, we described the IVPs of these women, identified by using our newly developed instrument: the Vaginal Cleansing Practices Questionnaire. The associations between the VM and IVPs were explored by comparing the alpha diversities, beta diversities, and the relative abundances at both the community level and individual genus level. RESULTS: The most abundant known bacterial genus found in the VM samples was Lactobacillus (35.7%), followed by Prevotella (21.4%). Eleven women (52%) reported using at least one type of IVP since menopause. The most common type of IVP was soap and water to clean inside the vagina. The use of IVPs was not associated with any alpha diversity metric, including Shannon index, inverse Simpson index, and Chao1 index; beta diversity metric, including Bray-Curtis and Jaccard distances; nor relative abundances at the community and individual genus level. Sociodemographic factors were also not associated with any alpha diversity metric. DISCUSSION: Clinicians must assess IVPs and other vaginal and sexual hygiene practices of women of all ages to educate and promote healthy behaviors. More than half of the postmenopausal women in this pilot study use IVPs. Understanding the reasoning behind participants' use of IVPs and their perceptions of the possible effects of these practices will require further research. Although the small sample did not show associations with the VM, more extensive studies are warranted.

Comparisons of Depression, Sexual Function, and Quality of Life Between Women With Gynecological Cancers and Race-Matched Healthy Controls.

BACKGROUND: Although higher incidence and mortality of gynecological cancer (GynCa) are documented in black compared with white women, few studies have documented quality of life (QOL) or healthy control comparisons. OBJECTIVE: This study compared depression, sexual function, and QOL between patients with GynCa and race-matched healthy controls. METHODS: Patients with GynCa and healthy controls completed the Patient Health Questionnaire-9, Female Sexual Function Index, and Functional Assessment of Cancer Therapy-General measures at baseline; GynCa patients were assessed again at 6 months post-radiation therapy (RT). RESULTS: Analyses included 84 participants (51% white, 49% black), including 28 GynCa patients and 56 controls with similar marital status. Compared with healthy controls, patients were younger, had a higher body mass index, and had more depression (P = .01); 82% of the patients and 71% of the healthy controls met criteria for sexual dysfunction at baseline (P = .29). Patients pre-RT had greater sexual dysfunction and lower QOL (P = .001) than controls did; patients at 6-month post-RT showed improved sexual function scores compared with pre-RT, with similar results to controls. White GynCa patients reported less sexual desire (P = .02), more pain (P = .05), and lower total Female Sexual Function Index scores (P = .01) than did black GynCa patients. Both black and white GynCa patients reported lower total QOL than their race-matched controls did (P = .07 and P = .002). CONCLUSIONS: Women with GynCa reported more depression and lower QOL than did healthy controls pre-RT. Among GynCa patients, white women had more sexual dysfunction than black women did. IMPLICATIONS FOR PRACTICE: The differences in sexual dysfunction between white and black women with GynCa suggest developing guidelines directing routine sexual assessment and rehabilitation in women treated for GynCa.

Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease.

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection.

Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease.

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection.

Automated generation of gene summaries at the Alliance of Genome Resources.

Short paragraphs that describe gene function, referred to as gene summaries, are valued by users of biological knowledgebases for the ease with which they convey key aspects of gene function. Manual curation of gene summaries, while desirable, is difficult for knowledgebases to sustain. We developed an algorithm that uses curated, structured gene data at the Alliance of Genome Resources (Alliance; www.alliancegenome.org) to automatically generate gene summaries that simulate natural language. The gene data used for this purpose include curated associations (annotations) to ontology terms from the Gene Ontology, Disease Ontology, model organism knowledgebase (MOK)-specific anatomy ontologies and Alliance orthology data. The method uses sentence templates for each data category included in the gene summary in order to build a natural language sentence from the list of terms associated with each gene. To improve readability of the summaries when numerous gene annotations are present, we developed a new algorithm that traverses ontology graphs in order to group terms by their common ancestors. The algorithm optimizes the coverage of the initial set of terms and limits the length of the final summary, using measures of information content of each ontology term as a criterion for inclusion in the summary. The automated gene summaries are generated with each Alliance release, ensuring that they reflect current data at the Alliance. Our method effectively leverages category-specific curation efforts of the Alliance member databases to create modular, structured and standardized gene summaries for seven member species of the Alliance. These automatically generated gene summaries make cross-species gene function comparisons tenable and increase discoverability of potential models of human disease. In addition to being displayed on Alliance gene pages, these summaries are also included on several MOK gene pages.

Comparison of vaginal microbiota in gynecologic cancer patients pre- and post-radiation therapy and healthy women.

BACKGROUND: While the importance of commensal microbes in vaginal health is well appreciated, little is known about the effects of gynecological cancer (GynCa) and radiation therapy (RT) on the vaginal microbiome (VM) of postmenopausal women. METHODS: We studied women with GynCa, pre- (N = 65) and post-RT (N = 25) and a group of healthy controls (N = 67) by sequencing the V4 region of the 16S rRNA gene from vaginal swabs and compared the diversity and composition of VMs between the three groups accounting for potential confounding factors in multivariate analysis of variance. RESULTS: Comparisons of cancer vs healthy groups revealed that Lactobacillus and Bifidobacterium have significantly higher relative abundance in the healthy group, while the cancer group was enriched in 16 phylogroups associated with bacterial vaginosis (BV) and inflammation, including Sneathia, Prevotella, Peptoniphilus, Fusobacterium, Anaerococcus, Dialister, Moryella, and Peptostreptococcus. In our sample, RT affected the α-diversity and correlated with higher abundance of typically rare VM species, including several members of the Lacnospiraceae family, a taxon previously linked to vaginal dysbiosis. In addition to cancer and treatment modalities, age and vaginal pH were identified as significant parameters that structure the VM. CONCLUSIONS: This is among the first reports identifying VM changes among postmenopausal women with cancer. RT alone seems to affect several phylogroups (12 bacterial genera), while gynecological cancer and its treatment modalities are associated with even greater significant shifts in the vaginal microbiota including the enrichment of opportunistic bacterial pathogens, which warrants further attention.

Addressing the Gap in Physician Preparedness To Assess Cardiovascular Risk in Women: a Comprehensive Approach to Cardiovascular Risk Assessment in Women.

PURPOSE OF REVIEW: Increased recognition of risk factors and improved knowledge of sex-specific presentations has led to improved clinical outcomes for women with cardiovascular disease (CVD) compared to two decades ago. Yet, CVD remains the leading cause of death for women in the USA. Women have unique risk factors for CVD that continue to go under-recognized by their physicians. RECENT FINDINGS: In a nationwide survey of primary care physicians (PCPs) and cardiologists, only 22% of PCPs and 42% of cardiologists reported being extremely well prepared to assess CVD risk in women. A presidential advisory from the American Heart Association (AHA) and American College of Obstetrics and Gynecologist (ACOG) recommends that cardiologists and obstetricians and gynecologists (Ob/Gyns) collaborate to promote CVD risk identification and reduction throughout a woman's lifetime. We suggest a comprehensive approach to identify unique and traditional risk factors for CVD in women, address the gap in physician knowledge, and improve cardiovascular care for women.

Corrigendum: High-throughput discovery of novel developmental phenotypes.

This corrects the article DOI: 10.1038/nature19356.

High-throughput discovery of novel developmental phenotypes.

Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

Application of comparative biology in GO functional annotation: the mouse model.

The Gene Ontology (GO) is an important component of modern biological knowledge representation with great utility for computational analysis of genomic and genetic data. The Gene Ontology Consortium (GOC) consists of a large team of contributors including curation teams from most model organism database groups as well as curation teams focused on representation of data relevant to specific human diseases. Key to the generation of consistent and comprehensive annotations is the development and use of shared standards and measures of curation quality. The GOC engages all contributors to work to a defined standard of curation that is presented here in the context of annotation of genes in the laboratory mouse. Comprehensive understanding of the origin, epistemology, and coverage of GO annotations is essential for most effective use of GO resources. Here the application of comparative approaches to capturing functional data in the mouse system is described.

Orthology for comparative genomics in the mouse genome database.

The mouse genome database (MGD) is the model organism database component of the mouse genome informatics system at The Jackson Laboratory. MGD is the international data resource for the laboratory mouse and facilitates the use of mice in the study of human health and disease. Since its beginnings, MGD has included comparative genomics data with a particular focus on human-mouse orthology, an essential component of the use of mouse as a model organism. Over the past 25 years, novel algorithms and addition of orthologs from other model organisms have enriched comparative genomics in MGD data, extending the use of orthology data to support the laboratory mouse as a model of human biology. Here, we describe current comparative data in MGD and review the history and refinement of orthology representation in this resource.

Methodology for the inference of gene function from phenotype data.

BACKGROUND: Biomedical ontologies are increasingly instrumental in the advancement of biological research primarily through their use to efficiently consolidate large amounts of data into structured, accessible sets. However, ontology development and usage can be hampered by the segregation of knowledge by domain that occurs due to independent development and use of the ontologies. The ability to infer data associated with one ontology to data associated with another ontology would prove useful in expanding information content and scope. We here focus on relating two ontologies: the Gene Ontology (GO), which encodes canonical gene function, and the Mammalian Phenotype Ontology (MP), which describes non-canonical phenotypes, using statistical methods to suggest GO functional annotations from existing MP phenotype annotations. This work is in contrast to previous studies that have focused on inferring gene function from phenotype primarily through lexical or semantic similarity measures. RESULTS: We have designed and tested a set of algorithms that represents a novel methodology to define rules for predicting gene function by examining the emergent structure and relationships between the gene functions and phenotypes rather than inspecting the terms semantically. The algorithms inspect relationships among multiple phenotype terms to deduce if there are cases where they all arise from a single gene function. We apply this methodology to data about genes in the laboratory mouse that are formally represented in the Mouse Genome Informatics (MGI) resource. From the data, 7444 rule instances were generated from five generalized rules, resulting in 4818 unique GO functional predictions for 1796 genes. CONCLUSIONS: We show that our method is capable of inferring high-quality functional annotations from curated phenotype data. As well as creating inferred annotations, our method has the potential to allow for the elucidation of unforeseen, biologically significant associations between gene function and phenotypes that would be overlooked by a semantics-based approach. Future work will include the implementation of the described algorithms for a variety of other model organism databases, taking full advantage of the abundance of available high quality curated data.

Capturing cancer initiating events in OncoCL, a cancer cell ontology.

We have developed an ontology, OncoCL, to classify cancer cells and provide a framework for consistent annotation of cancer-associated data from conventional surgical pathology and cancer molecular biology for the purpose of access, comparison, and analysis. The cell type ontology, CL, describes normal cell types and was not designed to capture the pathology of cancer cells. OncoCL builds upon CL, as a canonical cell (represented in CL) undergoes oncogenic change and tumorigenesis with the acquisition of the cancer hallmarks described by Hanahan and Weinberg.

Integration of cell line and clinical trial genome-wide analyses supports a polygenic architecture of Paclitaxel-induced sensory peripheral neuropathy.

PURPOSE: We sought to show the relevance of a lymphoblastoid cell line (LCL) model in the discovery of clinically relevant genetic variants affecting chemotherapeutic response by comparing LCL genome-wide association study (GWAS) results to clinical GWAS results. EXPERIMENTAL DESIGN: A GWAS of paclitaxel-induced cytotoxicity was conducted in 247 LCLs from the HapMap Project and compared with a GWAS of sensory peripheral neuropathy in patients with breast cancer (n = 855) treated with paclitaxel in the Cancer and Leukemia Group B (CALGB) 40101 trial. Significant enrichment was assessed by permutation resampling analysis. RESULTS: We observed an enrichment of LCL cytotoxicity-associated single-nucleotide polymorphisms (SNP) in the sensory peripheral neuropathy-associated SNPs from the clinical trial with concordant allelic directions of effect (empirical P = 0.007). Of the 24 SNPs that overlap between the clinical trial (P < 0.05) and the preclinical cytotoxicity study (P < 0.001), 19 of them are expression quantitative trait loci (eQTL), which is a significant enrichment of this functional class (empirical P = 0.0447). One of these eQTLs is located in RFX2, which encodes a member of the DNA-binding regulatory factor X family. Decreased expression of this gene by siRNA resulted in increased sensitivity of Neuroscreen-1(NS-1; rat pheochromocytoma) cells to paclitaxel as measured by reduced neurite outgrowth and increased cytotoxicity, functionally validating the involvement of RFX2 in nerve cell response to paclitaxel. CONCLUSIONS: The enrichment results and functional example imply that cellular models of chemotherapeutic toxicity may capture components of the underlying polygenic architecture of related traits in patients.

Disease model curation improvements at Mouse Genome Informatics.

Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in Man (OMIM) to curate mouse models of human disease. While OMIM provides highly detailed disease records that are familiar to many in the medical community, it lacks structure to support multilevel annotation. To improve disease annotation at MGI, we evaluated the merged Medical Subject Headings (MeSH) and OMIM disease vocabulary created by the Comparative Toxicogenomics Database (CTD) project. Overlaying MeSH onto OMIM provides hierarchical access to broad disease terms, a feature missing from the OMIM. We created an extended version of the vocabulary to meet the genetic disease-specific curation needs at MGI. Here we describe our evaluation of the CTD application, the extensions made by MGI and discuss the strengths and weaknesses of this approach. DATABASE URL: http://www.informatics.jax.org/

Cost-related medication underuse: prevalence among hospitalized managed care patients.

BACKGROUND: The affordability of prescription medications continues to be a major public health issue in the United States. Estimates of cost-related medication underuse come largely from surveys of ambulatory patients. Hospitalized patients may be vulnerable to cost-related underuse and its consequences, but have been subject to little investigation. OBJECTIVE: To determine impact of medication costs in a cohort of hospitalized managed care beneficiaries. METHODS: We surveyed consecutive patients admitted to medical services at an academic medical center. Questions about cost-related underuse were based on validated measures; predictors were assessed with multivariable models. Participants were asked about strategies to improve medication affordability, and were contacted after discharge to determine if they had filled newly prescribed medications. RESULTS: One-hundred thirty (41%) of 316 potentially eligible patients participated; 93 (75%) of these completed postdischarge surveys. Thirty patients (23%) reported cost-related underuse in the year prior to admission. In adjusted analyses, patients of black race were 3.39 times (95% confidence interval [CI], 1.05 to 11.02) more likely to report cost-related underuse than non-Hispanic white patients. Virtually all respondents (n = 123; 95%) endorsed at least 1 strategy to make medications more affordable. Few (16%) patients, prescribed medications at discharge, knew how much they would pay at the pharmacy. Almost none had spoken to their inpatient (4%) or outpatient (2%) providers about the cost of newly prescribed drugs. CONCLUSIONS: Cost-related underuse is common among hospitalized patients. Individuals of black race appear to be particularly at risk. Strategies should be developed to address this issue around the time of hospital discharge.

Chemotherapeutic-induced apoptosis: a phenotype for pharmacogenomics studies.

AIM: To determine whether cellular apoptosis is a suitable phenotypic trait for pharmacogenomics studies by evaluating caspase 3/7-mediated activity in lymphoblastoid cell lines after treatment with six chemotherapeutic agents: 5'-deoxyfluorouridine, pemetrexed, cytarabine, paclitaxel, carboplatin, and cisplatin. MATERIALS AND METHODS: Using monozygotic twin pair and sibling pair lymphoblastoid cell lines, we identified conditions for measurement of caspase 3/7 activity in lymphoblastoid cell lines. Genome-wide association studies were performed with over 2 million single nucleotide polymorphisms (SNPs) and cisplatin-induced apoptosis in HapMap CEU cell lines (n=77). RESULTS: Although treatment with 5'-deoxyfluorouridine and pemetrexed for up to 24 h resulted in low levels of apoptosis or interindividual variation in caspase-dependent cell death; paclitaxel, cisplatin, carboplatin, and cytarabine treatment for 24 h resulted in 9.4-fold, 9.1-fold, 7.0-fold, and 6.0-fold increases in apoptosis relative to control, respectively. There was a weak correlation between caspase activity and cytotoxicity (r(2)=0.03-0.29) demonstrating that cytotoxicity and apoptosis are two distinct phenotypes that may produce independent genetic associations. Estimated heritability (h(2)) for apoptosis was 0.57 and 0.29 for cytarabine (5 and 40 µmol/l, respectively), 0.22 for paclitaxel (12.5 nmol/l), and 0.34 for cisplatin (5 µmol/l). In the genome-wide association study using the HapMap CEU panel, we identified a significant enrichment of cisplatin-induced cytotoxicity SNPs within the significant cisplatin-induced apoptosis SNPs and an enrichment of expression quantitative trait loci (eQTL). Among these eQTLs, we identified several eQTLs with known function related to apoptosis and/or cytotoxicity. CONCLUSION: Our study identifies apoptosis as a phenotype for pharmacogenomic studies in lymphoblastoid cell lines after treatment with paclitaxel, cisplatin, carboplatin, and cytarabine that may have utility for discovering biomarkers to predict response to certain chemotherapeutics.