Assessment of BRCA1 and BRCA2 Germline Variant Data From Patients With Breast Cancer in a Real-World Data Registry.

PURPOSE: The emergence of large real-world clinical databases and tools to mine electronic medical records has allowed for an unprecedented look at large data sets with clinical and epidemiologic correlates. In clinical cancer genetics, real-world databases allow for the investigation of prevalence and effectiveness of prevention strategies and targeted treatments and for the identification of barriers to better outcomes. However, real-world data sets have inherent biases and problems (eg, selection bias, incomplete data, measurement error) that may hamper adequate analysis and affect statistical power. METHODS: Here, we leverage a real-world clinical data set from a large health network for patients with breast cancer tested for variants in BRCA1 and BRCA2 (N = 12,423). We conducted data cleaning and harmonization, cross-referenced with publicly available databases, performed variant reassessment and functional assays, and used functional data to inform a variant's clinical significance applying American College of Medical Geneticists and the Association of Molecular Pathology guidelines. RESULTS: In the cohort, White and Black patients were over-represented, whereas non-White Hispanic and Asian patients were under-represented. Incorrect or missing variant designations were the most significant contributor to data loss. While manual curation corrected many incorrect designations, a sizable fraction of patient carriers remained with incorrect or missing variant designations. Despite the large number of patients with clinical significance not reported, original reported clinical significance assessments were accurate. Reassessment of variants in which clinical significance was not reported led to a marked improvement in data quality. CONCLUSION: We identify the most common issues with BRCA1 and BRCA2 testing data entry and suggest approaches to minimize data loss and keep interpretation of clinical significance of variants up to date.

Assessment of small in-frame indels and C-terminal nonsense variants of BRCA1 using a validated functional assay.

BRCA1 (Breast Cancer 1, early onset) is linked to breast and ovarian cancer predisposition. Still, the risks conferred by a significant portion of BRCA1 variants identified in the population remains unknown. Most of these variants of uncertain significance are missense alterations. However, the functional implications of small in-frame deletions and/or insertions (indels) are also difficult to predict. Our group has previously evaluated the functional impact of 347 missense variants using an extensively validated transcriptional activity assay. Here we show a systematic assessment of 30 naturally occurring in-frame indels located at the C-terminal region of BRCA1. We identified positions sensitive and tolerant to alterations, expanding the knowledge of structural determinants of BRCA1 function. We further designed and assessed the impact of four single codon deletions in the tBRCT linker region and six nonsense variants at the C-terminus end of BRCA1. Amino acid substitutions, deletions or insertions in the disordered region do not significantly impact activity and are not likely to constitute pathogenic alleles. On the other hand, a sizeable fraction of in-frame indels at the BRCT domain significantly impact function. We then use a Bayesian integrative statistical model to derive the probability of pathogenicity for each variant. Our data highlights the importance of assessing the impact of small in-frame indels in BRCA1 to improve risk assessment and clinical decisions for carriers.

An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance.

Loss-of-function variants in the BRCA1 and BRCA2 susceptibility genes predispose carriers to breast and/or ovarian cancer. The use of germline testing panels containing these genes has grown dramatically, but the interpretation of the results has been complicated by the identification of many sequence variants of undefined cancer relevance, termed "Variants of Uncertain Significance (VUS)." We have developed functional assays and a statistical model called VarCall for classifying BRCA1 and BRCA2 VUS. Here we describe a multifactorial extension of VarCall, called VarCall XT, that allows for co-analysis of multiple forms of genetic evidence. We evaluated the accuracy of models defined by the combinations of functional, in silico protein predictors, and family data for VUS classification. VarCall XT classified variants of known pathogenicity status with high sensitivity and specificity, with the functional assays contributing the greatest predictive power. This approach could be used to identify more patients that would benefit from personalized cancer risk assessment and management.

Integration of functional assay data results provides strong evidence for classification of hundreds of BRCA1 variants of uncertain significance.

PURPOSE: BRCA1 pathogenic variant heterozygotes are at a substantially increased risk for breast and ovarian cancer. The widespread uptake of testing has led to a significant increase in the detection of missense variants in BRCA1, the vast majority of which are variants of uncertain clinical significance (VUS), posing a challenge to genetic counseling. Here, we harness a wealth of functional data for thousands of variants to aid in variant classification. METHODS: We have collected, curated, and harmonized functional data for 2701 missense variants representing 24.5% of possible missense variants in BRCA1. Results were harmonized across studies by converting data into binary categorical variables (functional impact versus no functional impact). Using a panel of reference variants we identified a subset of assays with high sensitivity and specificity (≥80%) and apply the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant interpretation guidelines to assign evidence criteria for classification. RESULTS: Integration of data from validated assays provided ACMG/AMP evidence criteria in favor of pathogenicity for 297 variants or against pathogenicity for 2058 representing 96.2% of current VUS functionally assessed. We also explore discordant results and identify limitations in the approach. CONCLUSION: High quality functional data are available for BRCA1 missense variants and provide evidence for classification of 2355 VUS according to their pathogenicity.

A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays.

Sequencing-based genetic tests to identify individuals at increased risk of hereditary breast and ovarian cancers have resulted in the identification of more than 40,000 sequence variants of BRCA1 and BRCA2. A majority of these variants are considered to be variants of uncertain significance (VUS) because their impact on disease risk remains unknown, largely due to lack of sufficient familial linkage and epidemiological data. Several assays have been developed to examine the effect of VUS on protein function, which can be used to assess their impact on cancer susceptibility. In this study, we report the functional characterization of 88 BRCA2 variants, including several previously uncharacterized variants, using a well-established mouse embryonic stem cell (mESC)-based assay. We have examined their ability to rescue the lethality of Brca2 null mESC as well as sensitivity to six DNA damaging agents including ionizing radiation and a PARP inhibitor. We have also examined the impact of BRCA2 variants on splicing. In addition, we have developed a computational model to determine the probability of impact on function of the variants that can be used for risk assessment. In contrast to the previous VarCall models that are based on a single functional assay, we have developed a new platform to analyze the data from multiple functional assays separately and in combination. We have validated our VarCall models using 12 known pathogenic and 10 neutral variants and demonstrated their usefulness in determining the pathogenicity of BRCA2 variants that are listed as VUS or as variants with conflicting functional interpretation.

Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling.

By replacing lost or dysfunctional myocardium, tissue regeneration is a promising approach to treat heart failure. However, the challenge of detecting bona fide heart regeneration limits the validation of potential regenerative factors. One method to detect new cardiomyocytes is multicolor lineage tracing with clonal analysis. Clonal analysis experiments can be difficult to undertake, because labeling conditions that are too sparse lack sensitivity for rare events such as cardiomyocyte proliferation, and diffuse labeling limits the ability to resolve clones. Presented here is a protocol to undertake clonal analysis of the neonatal mouse heart by using statistical modeling of nearest neighbor distributions to resolve cardiomyocyte clones. This approach enables resolution of clones over a range of labeling conditions and provides a robust analytical approach for quantifying cardiomyocyte proliferation and regeneration. This protocol can be adapted to other tissues and can be broadly used to study tissue regeneration.

Artificial habitats host elevated densities of large reef-associated predators.

Large predators play important ecological roles, yet many are disproportionately imperiled. In marine systems, artificial reefs are often deployed to restore degraded reefs or supplement existing reefs, but it remains unknown whether these interventions benefit large predators. Comparative field surveys of thirty artificial and natural reefs across ~200 km of the North Carolina, USA coast revealed large reef-associated predators were more dense on artificial than natural reefs. This pattern was associated with higher densities of transient predators (e.g. jacks, mackerel, barracuda, sharks) on artificial reefs, but not of resident predators (e.g., grouper, snapper). Further analyses revealed that this pattern of higher transient predator densities on artificial reefs related to reef morphology, as artificial reefs composed of ships hosted higher transient predator densities than concrete reefs. The strength of the positive association between artificial reefs and transient predators increased with a fundamental habitat trait-vertical extent. Taller artificial reefs had higher densities of transient predators, even when accounting for habitat area. A global literature review of high trophic level fishes on artificial and natural habitats suggests that the overall pattern of more predators on artificial habitats is generalizable. Together, these findings provide evidence that artificial habitats, especially those like sunken ships that provide high vertical structure, may support large predators.

The Risk of Ovarian Cancer Increases with an Increase in the Lifetime Number of Ovulatory Cycles: An Analysis from the Ovarian Cancer Cohort Consortium (OC3).

Repeated exposure to the acute proinflammatory environment that follows ovulation at the ovarian surface and distal fallopian tube over a woman's reproductive years may increase ovarian cancer risk. To address this, analyses included individual-level data from 558,709 naturally menopausal women across 20 prospective cohorts, among whom 3,246 developed invasive epithelial ovarian cancer (2,045 serous, 319 endometrioid, 184 mucinous, 121 clear cell, 577 other/unknown). Cox models were used to estimate multivariable-adjusted HRs between lifetime ovulatory cycles (LOC) and its components and ovarian cancer risk overall and by histotype. Women in the 90th percentile of LOC (>514 cycles) were almost twice as likely to be diagnosed with ovarian cancer than women in the 10th percentile (<294) [HR (95% confidence interval): 1.92 (1.60-2.30)]. Risk increased 14% per 5-year increase in LOC (60 cycles) [(1.10-1.17)]; this association remained after adjustment for LOC components: number of pregnancies and oral contraceptive use [1.08 (1.04-1.12)]. The association varied by histotype, with increased risk of serous [1.13 (1.09-1.17)], endometrioid [1.20 (1.10-1.32)], and clear cell [1.37 (1.18-1.58)], but not mucinous [0.99 (0.88-1.10), P-heterogeneity = 0.01] tumors. Heterogeneity across histotypes was reduced [P-heterogeneity = 0.15] with adjustment for LOC components [1.08 serous, 1.11 endometrioid, 1.26 clear cell, 0.94 mucinous]. Although the 10-year absolute risk of ovarian cancer is small, it roughly doubles as the number of LOC rises from approximately 300 to 500. The consistency and linearity of effects strongly support the hypothesis that each ovulation leads to small increases in the risk of most ovarian cancers, a risk that cumulates through life, suggesting this as an important area for identifying intervention strategies. SIGNIFICANCE: Although ovarian cancer is rare, risk of most ovarian cancers doubles as the number of lifetime ovulatory cycles increases from approximately 300 to 500. Thus, identifying an important area for cancer prevention research.

Bridging the gaps: using an NHP model to predict single dose radiation absorption in humans.

Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation.Materials and Methods: We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species.Results: We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device.Conclusions: Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation.

Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk.

BACKGROUND: Germline DNA copy number variation (CNV) is a ubiquitous source of genetic variation and remains largely unexplored in association with epithelial ovarian cancer (EOC) risk. METHODS: CNV was quantified in the DNA of approximately 3,500 cases and controls genotyped with the Illumina 610k and HumanOmni2.5M arrays. We performed a genome-wide association study of common (>1%) CNV regions (CNVRs) with EOC and high-grade serous (HGSOC) risk and, using The Cancer Genome Atlas (TCGA), performed in silico analyses of tumor-gene expression. RESULTS: Three CNVRs were associated (P < 0.01) with EOC risk: two large (∼100 kb) regions within the 610k set and one small (<5 kb) region with the higher resolution 2.5M data. Large CNVRs included a duplication at LILRA6 (OR = 2.57; P = 0.001) and a deletion at CYP2A7 (OR = 1.90; P = 0.007) that were strongly associated with HGSOC risk (OR = 3.02; P = 8.98 × 10-5). Somatic CYP2A7 alterations correlated with EGLN2 expression in tumors (P = 2.94 × 10-47). An intronic ERBB4/HER4 deletion was associated with reduced EOC risk (OR = 0.33; P = 9.5 × 10-2), and somatic deletions correlated with ERBB4 downregulation (P = 7.05 × 10-5). Five CNVRs were associated with HGSOC, including two reduced-risk deletions: one at 1p36.33 (OR = 0.28; P = 0.001) that correlated with lower CDKIIA expression in TCGA tumors (P = 2.7 × 10-7), and another at 8p21.2 (OR = 0.52; P = 0.002) that was present somatically where it correlated with lower GNRH1 expression (P = 5.9 × 10-5). CONCLUSIONS: Though CNV appears to not contribute largely to EOC susceptibility, a number of low-to-common frequency variants may influence the risk of EOC and tumor-gene expression. IMPACT: Further research on CNV and EOC susceptibility is warranted, particularly with CNVs estimated from high-density arrays.

Impact of amino acid substitutions at secondary structures in the BRCT domains of the tumor suppressor BRCA1: Implications for clinical annotation.

Genetic testing for BRCA1, a DNA repair protein, can identify carriers of pathogenic variants associated with a substantially increased risk for breast and ovarian cancers. However, an association with increased risk is unclear for a large fraction of BRCA1 variants present in the human population. Most of these variants of uncertain clinical significance lead to amino acid changes in the BRCA1 protein. Functional assays are valuable tools to assess the potential pathogenicity of these variants. Here, we systematically probed the effects of substitutions in the C terminus of BRCA1: the N- and C-terminal borders of its tandem BRCT domain, the BRCT-[N-C] linker region, and the α1 and α'1 helices in BRCT-[N] and -[C]. Using a validated transcriptional assay based on a fusion of the GAL4 DNA-binding domain to the BRCA1 C terminus (amino acids 1396-1863), we assessed the functional impact of 99 missense variants of BRCA1. We include the data obtained for these 99 missense variants in a joint analysis to generate the likelihood of pathogenicity for 347 missense variants in BRCA1 using VarCall, a Bayesian integrative statistical model. The results from this analysis increase our understanding of BRCA1 regions less tolerant to changes, identify functional borders of structural domains, and predict the likelihood of pathogenicity for 98% of all BRCA1 missense variants in this region recorded in the population. This knowledge will be critical for improving risk assessment and clinical treatment of carriers of BRCA1 variants.

Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches.

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

TRPV1 temperature activation is specifically sensitive to strong decreases in amino acid hydrophobicity.

Several transient receptor potential (TRP) ion channels can be directly activated by hot or cold temperature with high sensitivity. However, the structures and molecular mechanism giving rise to their high temperature sensitivity are not fully understood. One hypothesized mechanism assumes that temperature activation is driven by the exposure of hydrophobic residues to solvent. This mechanism further predicts that residues are exposed to solvent in a coordinated fashion, but without necessarily being located in close proximity to each other. However, there is little experimental evidence supporting this mechanism in TRP channels. Here, we combined high-throughput mutagenesis, functional screening, and deep sequencing to identify mutations from a total of ~7,300 TRPV1 random mutant clones. We found that strong decreases in hydrophobicity of amino acids are better tolerated for activation by capsaicin than for activation by hot temperature, suggesting that strong hydrophobicity might be specifically required for temperature activation. Altogether, our work provides initial correlative support for a previously hypothesized temperature mechanism in TRP ion channels.

Characterization of dependencies between growth and division in budding yeast.

Cell growth and division are processes vital to the proliferation and development of life. Coordination between these two processes has been recognized for decades in a variety of organisms. In the budding yeast Saccharomyces cerevisiae, this coordination or 'size control' appears as an inverse correlation between cell size and the rate of cell-cycle progression, routinely observed in G1 prior to cell division commitment. Beyond this point, cells are presumed to complete S/G2/M at similar rates and in a size-independent manner. As such, studies of dependence between growth and division have focused on G1 Moreover, in unicellular organisms, coordination between growth and division has commonly been analysed within the cycle of a single cell without accounting for correlations in growth and division characteristics between cycles of related cells. In a comprehensive analysis of three published time-lapse microscopy datasets, we analyse both intra- and inter-cycle dependencies between growth and division, revisiting assumptions about the coordination between these two processes. Interestingly, we find evidence (i) that S/G2/M durations are systematically longer in daughters than in mothers, (ii) of dependencies between S/G2/M and size at budding that echo the classical G1 dependencies, and (iii) in contrast with recent bacterial studies, of negative dependencies between size at birth and size accumulated during the cell cycle. In addition, we develop a novel hierarchical model to uncover inter-cycle dependencies, and we find evidence for such dependencies in cells growing in sugar-poor environments. Our analysis highlights the need for experimentalists and modellers to account for new sources of cell-to-cell variation in growth and division, and our model provides a formal statistical framework for the continued study of dependencies between biological processes.

DNA Methylation of Regulatory Regions of Imprinted Genes at Birth and Its Relation to Infant Temperament.

BACKGROUND: DNA methylation of the differentially methylated regions (DMRs) of imprinted genes is relevant to neurodevelopment. METHODS: DNA methylation status of the DMRs of nine imprinted genes in umbilical cord blood leukocytes was analyzed in relation to infant behaviors and temperament (n = 158). RESULTS: MEG3 DMR levels were positively associated with internalizing (ß = 0.15, P = 0.044) and surgency (ß = 0.19, P = 0.018) behaviors, after adjusting for birth weight, gender, gestational age at birth, maternal age at delivery, race/ethnicity, education level, smoking status, parity, and a history of anxiety or depression. Higher methylation levels at the intergenic MEG3-IG methylation regions were associated with surgency (ß = 0.28, P = 0.0003) and PEG3 was positively related to externalizing (ß = 0.20, P = 0.01) and negative affectivity (ß = 0.18, P = 0.02). CONCLUSION: While the small sample size limits inference, these pilot data support gene-specific associations between epigenetic differences in regulatory regions of imprinted domains at birth and later infant temperament.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Effects of Stone Size on the Comminution Process and Efficiency in Shock Wave Lithotripsy.

The effects of stone size on the process and comminution efficiency of shock wave lithotripsy (SWL) were investigated in experiments, numerical simulations and scale analysis. Cylindrical BegoStone phantoms with approximately equal height and diameter of either 4, 7 or 10 mm, in a total aggregated mass of about 1.5 g, were treated in an electromagnetic shock wave lithotripter field. The resultant stone comminution was found to correlate closely with the average peak pressure, P+(avg), incident on the stones. The P+(avg) threshold necessary to initiate stone fragmentation in water increased from 7.9 to 8.8 to 12.7 MPa, respectively, as stone size decreased from 10 to 7 to 4 mm. Similar changes in the P+(avg) threshold were observed for the 7- and 10-mm stones treated in 1,3-butanediol, in which cavitation is suppressed, suggesting that the observed size dependency is due to changes in stress distribution within stones of different size. Moreover, the slope of the correlation curve between stone comminution and ln(P¯+(avg)) in water increased with decreasing stone size, whereas the opposite trend was observed in 1,3-butanediol. The progression of stone comminution in SWL exhibited size-dependence: the 7- and 10-mm stones fragmented into progressively smaller pieces, whereas a significant portion (>30%) of the 4-mm stones reached a stalemate within the size range of 2.8 ∼ 4 mm, even after 1000 shocks. Analytical scaling considerations suggest size-dependent fragmentation behavior, a hypothesis further supported by numerical model calculations that reveal changing patterns of constructive and destructive wave interference and, thus, variations in the maximum tensile stress or stress integral produced in cylindrical and spherical stone of different sizes.

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk.

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 - 7). One of the most significant signals (Pall histologies = 1.01 × 10 - 13;Pserous = 3.54 × 10 - 14) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r2 = 0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 - 5 > P≥5.0 ×10 - 7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 - 5; PSKAT-o = 9.23 × 10 - 4) and KRT13 (PAML = 1.67 × 10 - 4; PSKAT-o = 1.07 × 10 - 5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

Association between Prepregnancy Body Mass Index and Gestational Weight Gain with Size, Tempo, and Velocity of Infant Growth: Analysis of the Newborn Epigenetic Study Cohort.

BACKGROUND: The first 1000 days of life is a critical period of infant growth that has been linked to future adult health. Understanding prenatal factors that contribute to variation in growth during this period could inform successful prevention strategies. METHODS: Prenatal and maternal characteristics, including prepregnancy obesity and gestational weight gain were evaluated in relation to weight growth trajectories during the first 24 months of life using the SuperImposition by Translation and Rotation (SITAR) method, which provides estimates of infant size, timing to peak velocity, and growth velocity. The study sample included 704 mother-infant dyads from a multiethnic prebirth cohort from the Southeastern United States. The total number of weight measures was 8670 (median number per child = 14). RESULTS: Several prenatal and maternal characteristics were linked with infant growth parameters. The primary findings show that compared to women with a prepregnancy BMI between 18 and 24.9, women with a prepregnancy BMI ≥40 had infants that were 8% larger during the first 24 months, a delayed tempo of around 9 days, and a slower velocity. Mothers who had greater than adequate gestational weight gain had infants that were 5% larger even after controlling for prepregnancy BMI and several other covariates. CONCLUSIONS: The findings contribute new data on the associations between gestational weight gain and aspects of early growth using the SITAR method, and support a growing consensus in the literature that both prepregnancy BMI and gestational weight gain relate independently to risk for greater postnatal weight growth.

A targeted genetic association study of epithelial ovarian cancer susceptibility.

BACKGROUND: Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci. RESULTS: At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p <5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p< 3x10-6). METHODS: A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure. CONCLUSION: Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance.