Integration of gray matter nodules into functional cortical circuits in periventricular heterotopia

Alterations in neuronal circuitry are recognized as an important substrate of many neurological disorders, including epilepsy. Patients with the developmental brain malformation of periventricular nodular heterotopia (PNH) often have both seizures and dyslexia, and there is evidence to suggest that aberrant neuronal connectivity underlies both of these clinical features. We used task-based functional MRI (fMRI) to determine whether heterotopic nodules of gray matter in this condition are integrated into functional cortical circuits. Blood oxygenation level-dependent (BOLD) fMRI was acquired in eight participants with PNH during the performance of reading-related tasks. Evidence of neural activation within heterotopic gray matter was identified, and regions of cortical coactivation were then mapped systematically. Findings were correlated with resting-state functional connectivity results and with performance on the fMRI reading-related tasks. Six participants (75%) demonstrated activation within at least one region of gray matter heterotopia. Cortical areas directly overlying the heterotopia were usually coactivated (60%), as were areas known to have functional connectivity to the heterotopia in the task-free resting state (73%). Six of seven (86%) primary task contrasts resulted in heterotopia activation in at least one participant. Activation was most commonly seen during rapid naming of visual stimuli, a characteristic impairment in this patient population. Our findings represent a systematic demonstration that heterotopic gray matter can be metabolically coactivated in a neuronal migration disorder associated with epilepsy and dyslexia. Gray matter nodules were most commonly coactivated with the anatomically overlying cortex and other regions with resting-state connectivity to heterotopia. These results have broader implications for understanding the network pathogenesis of both seizures and reading disabilities

Physiological consequences of abnormal connectivity in a developmental epilepsy

Objective Many forms of epilepsy are associated with aberrant neuronal connections, but the relationship between such pathological connectivity and the underlying physiological predisposition to seizures is unclear. We sought to characterize the cortical excitability profile of a developmental form of epilepsy known to have structural and functional connectivity abnormalities. Methods We employed transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) recording in 8 patients with epilepsy from periventricular nodular heterotopia and matched healthy controls. We used connectivity imaging findings to guide TMS targeting and compared the evoked responses to single-pulse stimulation from different cortical regions. Results Heterotopia patients with active epilepsy demonstrated a relatively augmented late cortical response that was greater than that of matched controls. This abnormality was specific to cortical regions with connectivity to subcortical heterotopic gray matter. Topographic mapping of the late response differences showed distributed cortical networks that were not limited to the stimulation site, and source analysis in 1 subject revealed that the generator of abnormal TMS-evoked activity overlapped with the spike and seizure onset zone. Interpretation Our findings indicate that patients with epilepsy from gray matter heterotopia have altered cortical physiology consistent with hyperexcitability, and that this abnormality is specifically linked to the presence of aberrant connectivity. These results support the idea that TMS-EEG could be a useful biomarker in epilepsy in gray matter heterotopia, expand our understanding of circuit mechanisms of epileptogenesis, and have potential implications for therapeutic neuromodulation in similar epileptic conditions associated with deep lesions

Identification of novel epithelial ovarian cancer loci in women of African ancestry.

Women of African ancestry have lower incidence of epithelial ovarian cancer (EOC) yet worse survival compared to women of European ancestry. We conducted a genome-wide association study in African ancestry women with 755 EOC cases, including 537 high-grade serous ovarian carcinomas (HGSOC) and 1,235 controls. We identified four novel loci with suggestive evidence of association with EOC (p < 1 × 10-6 ), including rs4525119 (intronic to AKR1C3), rs7643459 (intronic to LOC101927394), rs4286604 (12 kb 3' of UGT2A2) and rs142091544 (5 kb 5' of WWC1). For HGSOC, we identified six loci with suggestive evidence of association including rs37792 (132 kb 5' of follistatin [FST]), rs57403204 (81 kb 3' of MAGEC1), rs79079890 (LOC105376360 intronic), rs66459581 (5 kb 5' of PRPSAP1), rs116046250 (GABRG3 intronic) and rs192876988 (32 kb 3' of GK2). Among the identified variants, two are near genes known to regulate hormones and diseases of the ovary (AKR1C3 and FST), and two are linked to cancer (AKR1C3 and MAGEC1). In follow-up studies of the 10 identified variants, the GK2 region SNP, rs192876988, showed an inverse association with EOC in European ancestry women (p = 0.002), increased risk of ER positive breast cancer in African ancestry women (p = 0.027) and decreased expression of GK2 in HGSOC tissue from African ancestry women (p = 0.004). A European ancestry-derived polygenic risk score showed positive associations with EOC and HGSOC in women of African ancestry suggesting shared genetic architecture. Our investigation presents evidence of variants for EOC shared among European and African ancestry women and identifies novel EOC risk loci in women of African ancestry

Phenotypic assortment mediates the effect of social selection in a wild beetle population

Social interactions often have major fitness consequences, but little is known about how specific interacting phenotypes affect the strength of natural selection. Social influences on the evolutionary process can be assessed using a multilevel selection approach that partitions the effects of social partner phenotypes on fitness (referred to as social or group selection) from those of the traits of a focal individual (nonsocial or individual selection). To quantify the contribution of social selection to total selection affecting a trait, the patterns of phenotypic association among interactants must also be considered. We estimated selection gradients on male body size in a wild population of forked fungus beetles (Bolitotherus cornutus). We detected positive nonsocial selection and negative social selection on body size operating through differences in copulation success, indicating that large males with small social partners had highest fitness. In addition, we found that, in low-density demes, the phenotypes of focal individuals were negatively correlated with those of their social partners. This pattern reversed the negative effect of group selection on body size and led to stronger positive selection for body size. Our results demonstrate multilevel selection in nature and stress the importance of considering social selection whenever conspecific interactions occur nonrandomly

Inter-pathologist and pathology report agreement for ovarian tumor characteristics in the Nurses\u27 Health Studies.

BACKGROUND: Grade and histotype of ovarian carcinomas are often used as surrogates of molecular subtypes. We examined factors affecting pathologists\u27 reproducibility in two prospective studies. METHODS: Two pathologists independently reviewed slides from 459 incident ovarian cancers in the Nurses\u27 Health Study (NHS) and NHSII. We described agreement on tumor characteristics using percent agreement and Cohen\u27s standard kappa (κ) coefficients. We used logistic regression, with disagreement as the outcome, to evaluate the contribution of case and tumor characteristics to agreement. RESULTS: Inter-rater agreement was 95% (κ = 0.81) for carcinoma versus borderline, 89% (κ = 0.58) for grade and 85% (κ = 0.71) for histotype. Inter-rater grading disagreement was higher for non-serous histotypes (OR = 4.66, 95% CI 2.09-10.36) and lower for cancers with bizarre atypia (OR = 0.13, 95% CI 0.04-0.38). Agreement with original pathology reports was 94% (κ = 0.73) for carcinoma versus borderline, 78% (κ = 0.60) for histotype, and 79% (κ = 0.24) for grade. Grading disagreement was significantly lower for tumors with \u27solid, pseudoendometrioid or transitional\u27 (SET) architecture (OR = 0.08, 95%CI 0.01-0.84). Date of original diagnosis, hospital type, number of slides available for review, tumor stage, and slide quality were not related to agreement. CONCLUSION: Overall, inter-rater agreement for tumor type and grade for archival tissue specimens was good. Agreement between the consensus review and original pathology reports was lower. Factors contributing to grading disagreement included non-serous histotype, absence of bizarre atypia, and absence of SET architecture

Using Home Range Estimates To Construct Social Networks For Species With Indirect Behavioral Interactions

Social network analysis has become a vital tool for studying patterns of individual interactions that influence a variety of processes in behavior, ecology, and evolution. Taxa in which interactions are indirect or whose social behaviors are difficult to observe directly are being excluded from this rapidly expanding field. Here, we introduce a method that uses a probabilistic and spatially implicit technique for delineating social interactions. Kernel density estimators (KDE) are nonparametric techniques that are often used in home range analyses and allow researchers studying social networks to generate interaction matrices based on shared space use. We explored the use of KDE analysis and the effects of altering KDE input parameters on social network metrics using data from a natural population of the spatially persistent forked fungus beetle, Bolitotherus cornutus

Phenotypic Assortment Mediates The Effect Of Social Selection In A Wild Beetle Population

Social interactions often have major fitness consequences, but little is known about how specific interacting phenotypes affect the strength of natural selection. Social influences on the evolutionary process can be assessed using a multilevel selection approach that partitions the effects of social partner phenotypes on fitness (referred to as social or group selection) from those of the traits of a focal individual (nonsocial or individual selection). To quantify the contribution of social selection to total selection affecting a trait, the patterns of phenotypic association among interactants must also be considered. We estimated selection gradients on male body size in a wild population of forked fungus beetles (Bolitotherus cornutus). We detected positive nonsocial selection and negative social selection on body size operating through differences in copulation success, indicating that large males with small social partners had highest fitness. In addition, we found that, in low-density demes, the phenotypes of focal individuals were negatively correlated with those of their social partners. This pattern reversed the negative effect of group selection on body size and led to stronger positive selection for body size. Our results demonstrate multilevel selection in nature and stress the importance of considering social selection whenever conspecific interactions occur nonrandomly

Data from: Phenotypic assortment mediates the effect of social selection in a wild beetle population

Social interactions often have major fitness consequences, but little is known about how specific interacting phenotypes affect the strength of natural selection. Social influences on the evolutionary process can be assessed using a multilevel selection approach that partitions the effects of social partner phenotypes on fitness (referred to as social or group selection) from those of the traits of a focal individual (nonsocial or individual selection). To quantify the contribution of social selection to total selection affecting a trait, the patterns of phenotypic association among interactants must also be considered. We estimated selection gradients on male body size in a wild population of forked fungus beetles (Bolitotherus cornutus). We detected positive nonsocial selection and negative social selection on body size operating through differences in copulation success, indicating that large males with small social partners had highest fitness. In addition, we found that, in low-density demes, the phenotypes of focal individuals were negatively correlated with those of their social partners. This pattern reversed the negative effect of group selection on body size and led to stronger positive selection for body size. Our results demonstrate multilevel selection in nature and stress the importance of considering social selection whenever conspecific interactions occur nonrandomly.,deme-statsData used to generate Figure 3 and related statistics. Data collected from the wild and managed with JMP V.7male-male-interactionsFile used to calculate covariances, described as Cii and Cii (prime). Data collected in the wild and managed with JMP v7. Data used to generate figure Table 2 and used in calculation of Table 5.Social-selection-gradientData collected in the wild and managed with JMP v7. Data used in the calculation of Table 3, Table 4, and Table 5. These are the data used to calculate selection gradients. Also used to generate Figure 4.

Social-selection-gradient

Data collected in the wild and managed with JMP v7. Data used in the calculation of Table 3, Table 4, and Table 5. These are the data used to calculate selection gradients. Also used to generate Figure 4

male-male-interactions

File used to calculate covariances, described as Cii and Cii (prime). Data collected in the wild and managed with JMP v7. Data used to generate figure Table 2 and used in calculation of Table 5