Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort of toddlers.

Identifying factors linked to autism traits in the general population may improve our understanding of the mechanisms underlying divergent neurodevelopment. In this study we assess whether factors increasing the likelihood of childhood autism are related to early autistic trait emergence, or if other exposures are more important. We used data from 536 toddlers from London (UK), collected at birth (gestational age at birth, sex, maternal body mass index, age, parental education, parental language, parental history of neurodevelopmental conditions) and at 18 months (parents cohabiting, measures of socio-economic deprivation, measures of maternal parenting style, and a measure of maternal depression). Autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT) at 18 months. A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). In order to address variable collinearity we used principal component analysis, finding that a component which was positively correlated with Q-CHAT was also correlated to measures of parenting style and socio-economic deprivation. Our results show that parenting style and socio-economic deprivation correlate with the emergence of autism traits at age 18 months as measured with the Q-CHAT in a community sample.

Calcineurin promotes adaptation to chronic stress through two distinct mechanisms.

Adaptation to environmental stress requires coordination between stress-defense programs and cell cycle progression. The immediate response to many stressors has been well characterized, but how cells survive in challenging environments long-term is unknown. Here, we investigate the role of the stress-activated phosphatase calcineurin (CN) in adaptation to chronic CaCl2 stress in Saccharomyces cerevisiae. We find that prolonged exposure to CaCl2 impairs mitochondrial function and demonstrate that cells respond to this stressor using two CN-dependent mechanisms - one that requires the downstream transcription factor Crz1 and another that is Crz1-independent. Our data indicate that CN maintains cellular fitness by promoting cell cycle progression and preventing CaCl2-induced cell death. When Crz1 is present, transient CN activation suppresses cell death and promotes adaptation despite high levels of mitochondrial loss. However, in the absence of Crz1, prolonged activation of CN prevents mitochondrial loss and further cell death by upregulating glutathione (GSH) biosynthesis genes thereby mitigating damage from reactive oxygen species. These findings illustrate how cells maintain long-term fitness during chronic stress and suggest that CN promotes adaptation in challenging environments by multiple mechanisms.

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human error, and require considerable infrastructure. AIgarMIC streamlines and standardizes MIC measurement and is especially valuable for large-scale surveillance activities. MICs were measured using agar dilution for n = 10 antibiotics against clinical Enterobacterales isolates (n = 1,086) obtained from a large tertiary hospital microbiology laboratory. Escherichia coli (n = 827, 76%) was the most common organism. Photographs of agar plates were divided into smaller images covering one inoculation site. A labeled data set of colony images was created and used to train a convolutional neural network to classify images based on whether a bacterial colony was present (first-step model). If growth was present, a second-step model determined whether colony morphology suggested antimicrobial growth inhibition. The ability of the AI to determine MIC was then compared with standard visual determination. The first-step model classified bacterial growth as present/absent with 94.3% accuracy. The second-step model classified colonies as "inhibited" or "good growth" with 88.6% accuracy. For the determination of MIC, the rate of essential agreement was 98.9% (644/651), with a bias of -7.8%, compared with manual annotation. AIgarMIC uses artificial intelligence to automate endpoint assessments for agar dilution and potentially increases throughput without bespoke equipment. AIgarMIC reduces laboratory barriers to generating high-quality MIC data that can be used for large-scale surveillance programs. IMPORTANCE: This research uses modern artificial intelligence and machine-learning approaches to standardize and automate the interpretation of agar dilution minimum inhibitory concentration testing. Artificial intelligence is currently of significant topical interest to researchers and clinicians. In our manuscript, we demonstrate a use-case in the microbiology laboratory and present validation data for the model's performance against manual interpretation.

Functional genomic screens with death rate analyses reveal mechanisms of drug action.

A common approach for understanding how drugs induce their therapeutic effects is to identify the genetic determinants of drug sensitivity. Because 'chemo-genetic profiles' are performed in a pooled format, inference of gene function is subject to several confounding influences related to variation in growth rates between clones. In this study, we developed Method for Evaluating Death Using a Simulation-assisted Approach (MEDUSA), which uses time-resolved measurements, along with model-driven constraints, to reveal the combination of growth and death rates that generated the observed drug response. MEDUSA is uniquely effective at identifying death regulatory genes. We apply MEDUSA to characterize DNA damage-induced lethality in the presence and absence of p53. Loss of p53 switches the mechanism of DNA damage-induced death from apoptosis to a non-apoptotic death that requires high respiration. These findings demonstrate the utility of MEDUSA both for determining the genetic dependencies of lethality and for revealing opportunities to potentiate chemo-efficacy in a cancer-specific manner.

Heterogeneity and transcriptional drivers of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity, we defined transcriptional, epigenetic, and metabolic subtypes and subtype-driving super-enhancers and transcription factors by combining functional and molecular profiling with computational analyses. Single-cell RNA sequencing revealed relative homogeneity of the major transcriptional subtypes (luminal, basal, and mesenchymal) within samples. We found that mesenchymal TNBCs share features with mesenchymal neuroblastoma and rhabdoid tumors and that the PRRX1 transcription factor is a key driver of these tumors. PRRX1 is sufficient for inducing mesenchymal features in basal but not in luminal TNBC cells via reprogramming super-enhancer landscapes, but it is not required for mesenchymal state maintenance or for cellular viability. Our comprehensive, large-scale, multiplatform, multiomics study of both experimental and clinical TNBC is an important resource for the scientific and clinical research communities and opens venues for future investigation.

In Vivo Tumorigenicity of the 20q11.21 Amplicon in an Engraftment Model of hPSCs and Differentiated Liver Cells.

Human pluripotent stem cells (hPSCs) are a promising source of somatic cells for clinical applications and disease modelling. However, during culture they accumulate genetic aberrations such as amplification of 20q11.21 which occurs in approximately 20% of extensively cultured hPSC lines and confers a BCL2L1-mediated survival advantage. During the production of the large number of cells required for transplantation and therapy these aberrations may become unavoidable which has important safety implications for therapies and may also impact upon disease modelling. Presently, these risks are poorly understood; whilst it is apparent that large-scale genetic aberrations can pose an oncogenic risk, the risks associated with smaller, more insidious changes have not been fully explored. In this report, the effects of engraftment of human embryonic stem cells (hESCs) and hESC-derived hepatocyte-like cells (HLCs) with and without amplification of the 20q11.21 minimal amplicon and isochromosome 20q (i20q) in SCID-beige mice are presented. The cells were tracked in vivo using a luminescent reporter over a period of approximately four months. Intrasplenic injection of hESCs showed greater engraftment potential and the formation of more severely disruptive lesions in the liver and spleen of animals injected with cells containing 20q11.21 compared with i20q and wild type. HLCs with 20q11.21 engrafted more successfully and formed more severely disruptive lesions than wild type cells or cells with i20q. These results reinforce the notion that karyotyping of therapeutic hPSC is required for transplant, and suggest that screening for known common aberrations is necessary. Further work to identify commonly arising genetic aberrations should be performed and routine screening for hPSCs intended for therapeutic use should be used.

p53 controls choice between apoptotic and non-apoptotic death following DNA damage.

DNA damage can activate apoptotic and non-apoptotic forms of cell death; however, it remains unclear what features dictate which type of cell death is activated. We report that p53 controls the choice between apoptotic and non-apoptotic death following exposure to DNA damage. In contrast to the conventional model, which suggests that p53-deficient cells should be resistant to DNA damage-induced cell death, we find that p53-deficient cells die at high rates following DNA damage, but exclusively using non-apoptotic mechanisms. Our experimental data and computational modeling reveal that non-apoptotic death in p53-deficient cells has not been observed due to use of assays that are either insensitive to cell death, or that specifically score apoptotic cells. Using functional genetic screening - with an analysis that enables computational inference of the drug-induced death rate - we find in p53-deficient cells that DNA damage activates a mitochondrial respiration-dependent form of cell death, called MPT-driven necrosis. Cells deficient for p53 have high basal respiration, which primes MPT-driven necrosis. Finally, using metabolite profiling, we identified mitochondrial activity-dependent metabolic vulnerabilities that can be targeted to potentiate the lethality of DNA damage specifically in p53-deficient cells. Our findings reveal how the dual functions of p53 in regulating mitochondrial activity and the DNA damage response combine to facilitate the choice between apoptotic and non-apoptotic death.

JAK-STAT Signaling in Inflammatory Breast Cancer Enables Chemotherapy-Resistant Cell States.

Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. In breast cancer, CD44+CD24- cells possess stem cell-like features and contribute to disease progression, and we previously described a CD44+CD24-pSTAT3+ breast cancer cell subpopulation that is dependent on JAK2/STAT3 signaling. Here we report that CD44+CD24- cells are the most frequent cell type in IBC and are commonly pSTAT3+. Combination of JAK2/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. IBC cell lines resistant to paclitaxel and doxorubicin were developed and characterized to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed enrichment of genes associated with lineage identity and inflammation in chemotherapy-resistant derivatives. Integrated pSTAT3 chromatin immunoprecipitation sequencing and RNA sequencing (RNA-seq) analyses showed pSTAT3 regulates genes related to inflammation and epithelial-to-mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. Investigation of cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare preexisting subpopulations or an acquired change. Finally, combination treatment with paclitaxel and JAK2/STAT3 inhibition prevented the emergence of the mesenchymal chemo-resistant subpopulation. These results provide mechanistic rational for combination of chemotherapy with inhibition of JAK2/STAT3 signaling as a more effective therapeutic strategy in IBC. SIGNIFICANCE: Chemotherapy resistance in inflammatory breast cancer is driven by the JAK2/STAT3 pathway, in part via cAMP/PKA signaling and a cell state switch, which can be overcome using paclitaxel combined with JAK2 inhibitors.

Development of neonatal brain functional centrality and alterations associated with preterm birth.

Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

Breast cancer prevention by short-term inhibition of TGFß signaling.

Cancer prevention has a profound impact on cancer-associated mortality and morbidity. We previously identified TGFß signaling as a candidate regulator of mammary epithelial cells associated with breast cancer risk. Here, we show that short-term TGFBR inhibitor (TGFBRi) treatment of peripubertal ACI inbred and Sprague Dawley outbred rats induces lasting changes and prevents estrogen- and carcinogen-induced mammary tumors, respectively. We identify TGFBRi-responsive cell populations by single cell RNA-sequencing, including a unique epithelial subpopulation designated secretory basal cells (SBCs) with progenitor features. We detect SBCs in normal human breast tissues and find them to be associated with breast cancer risk. Interactome analysis identifies SBCs as the most interactive cell population and the main source of insulin-IGF signaling. Accordingly, inhibition of TGFBR and IGF1R decrease proliferation of organoid cultures. Our results reveal a critical role for TGFß in regulating mammary epithelial cells relevant to breast cancer and serve as a proof-of-principle cancer prevention strategy.

The Developing Human Connectome Project Neonatal Data Release.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Predicting age and clinical risk from the neonatal connectome.

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p < 0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p < 0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

Insights into Immune Escape During Tumor Evolution and Response to Immunotherapy Using a Rat Model of Breast Cancer.

Animal models are critical for the preclinical validation of cancer immunotherapies. Unfortunately, mouse breast cancer models do not faithfully reproduce the molecular subtypes and immune environment of the human disease. In particular, there are no good murine models of estrogen receptor-positive (ER+) breast cancer, the predominant subtype in patients. Here, we show that Nitroso-N-methylurea-induced mammary tumors in outbred Sprague-Dawley rats recapitulate the heterogeneity for mutational profiles, ER expression, and immune evasive mechanisms observed in human breast cancer. We demonstrate the utility of this model for preclinical studies by dissecting mechanisms of response to immunotherapy using combination TGFBR inhibition and PD-L1 blockade. Short-term treatment of early-stage tumors induced durable responses. Gene expression profiling and spatial mapping classified tumors as inflammatory and noninflammatory, and identified IFNγ, T-cell receptor (TCR), and B-cell receptor (BCR) signaling, CD74/MHC II, and epithelium-interacting CD8+ T cells as markers of response, whereas the complement system, M2 macrophage phenotype, and translation in mitochondria were associated with resistance. We found that the expression of CD74 correlated with leukocyte fraction and TCR diversity in human breast cancer. We identified a subset of rat ER+ tumors marked by expression of antigen-processing genes that had an active immune environment and responded to treatment. A gene signature characteristic of these tumors predicted disease-free survival in patients with ER+ Luminal A breast cancer and overall survival in patients with metastatic breast cancer receiving anti-PD-L1 therapy. We demonstrate the usefulness of this preclinical model for immunotherapy and suggest examination to expand immunotherapy to a subset of patients with ER+ disease. See related Spotlight by Roussos Torres, p. 672.

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies.

Infants born in early term (37-38 weeks gestation) experience slower neurodevelopment than those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain. Here we characterise brain volume and white matter correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome using T2 and diffusion weighted MRI acquired in the neonatal period from a cohort (n = 454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor-based morphometry and tract-based spatial statistics. Neurodevelopment was assessed at age 18 months using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Infants born earlier had higher relative ventricular volume and lower relative brain volume in the deep grey matter, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial, and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Regression models predicting outcome from gestational age at birth were significantly improved after adding neuroimaging features associated with gestational age at birth. This work adds to the body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

Simultaneous profiling of multiple chromatin proteins in the same cells.

Methods derived from CUT&RUN and CUT&Tag enable genome-wide mapping of the localization of proteins on chromatin from as few as one cell. These and other mapping approaches focus on one protein at a time, preventing direct measurements of co-localization of different chromatin proteins in the same cells and requiring prioritization of targets where samples are limiting. Here, we describe multi-CUT&Tag, an adaptation of CUT&Tag that overcomes these hurdles by using antibody-specific barcodes to simultaneously map multiple proteins in the same cells. Highly specific multi-CUT&Tag maps of histone marks and RNA Polymerase II uncovered sites of co-localization in the same cells, active and repressed genes, and candidate cis-regulatory elements. Single-cell multi-CUT&Tag profiling facilitated identification of distinct cell types from a mixed population and characterization of cell-type-specific chromatin architecture. In sum, multi-CUT&Tag increases the information content per cell of epigenomic maps, facilitating direct analysis of the interplay of different chromatin proteins.

The impact of tumor epithelial and microenvironmental heterogeneity on treatment responses in HER2+ breast cancer.

Despite the availability of multiple human epidermal growth factor receptor 2-targeted (HER2-targeted) treatments, therapeutic resistance in HER2+ breast cancer remains a clinical challenge. Intratumor heterogeneity for HER2 and resistance-conferring mutations in the PIK3CA gene (encoding PI3K catalytic subunit α) have been investigated in response and resistance to HER2-targeting agents, while the role of divergent cellular phenotypes and tumor epithelial-stromal cell interactions is less well understood. Here, we assessed the effect of intratumor cellular genetic heterogeneity for ERBB2 (encoding HER2) copy number and PIK3CA mutation on different types of neoadjuvant HER2-targeting therapies and clinical outcome in HER2+ breast cancer. We found that the frequency of cells lacking HER2 was a better predictor of response to HER2-targeted treatment than intratumor heterogeneity. We also compared the efficacy of different therapies in the same tumor using patient-derived xenograft models of heterogeneous HER2+ breast cancer and single-cell approaches. Stromal determinants were better predictors of response than tumor epithelial cells, and we identified alveolar epithelial and fibroblastic reticular cells as well as lymphatic vessel endothelial hyaluronan receptor 1-positive (Lyve1+) macrophages as putative drivers of therapeutic resistance. Our results demonstrate that both preexisting and acquired resistance to HER2-targeting agents involve multiple mechanisms including the tumor microenvironment. Furthermore, our data suggest that intratumor heterogeneity for HER2 should be incorporated into treatment design.

ELP-dependent expression of MCL1 promotes resistance to EGFR inhibition in triple-negative breast cancer cells.

Targeted therapeutics for cancer generally exploit "oncogene addiction," a phenomenon in which the growth and survival of tumor cells depend on the activity of a particular protein. However, the efficacy of oncogene-targeted therapies varies substantially. For instance, targeting epidermal growth factor receptor (EGFR) signaling is effective in some non-small cell lung cancer (NSCLC) but not in triple-negative breast cancer (TNBC), although these cancers show a similar degree of increase in EGFR activity. Using a genome-wide CRISPR-Cas9 genetic knockout screen, we found that the Elongator (ELP) complex mediates insensitivity to the EGFR inhibitor erlotinib in TNBC cells by promoting the synthesis of the antiapoptotic protein Mcl-1. Depleting ELP proteins promoted apoptotic cell death in an EGFR inhibition-dependent manner. Pharmacological inhibition of Mcl-1 synergized with EGFR inhibition in a panel of genetically diverse TNBC cells. The findings indicate that TNBC "addiction" to EGFR signaling is masked by the ELP complex and that resistance to EGFR inhibitors in TNBC might be overcome by cotargeting Mcl-1.

A functionally defined high-density NRF2 interactome reveals new conditional regulators of ARE transactivation.

NRF2 (NFE2L2) is a cytoprotective transcription factor associated with >60 human diseases, adverse drug reactions and therapeutic resistance. To provide insight into the complex regulation of NRF2 responses, 1962 predicted NRF2-partner interactions were systematically tested to generate an experimentally defined high-density human NRF2 interactome. Verification and conditional stratification of 46 new NRF2 partners was achieved by co-immunoprecipitation and the novel integration of quantitative data from dual luminescence-based co-immunoprecipitation (DULIP) assays and live-cell fluorescence cross-correlation spectroscopy (FCCS). The functional impact of new partners was then assessed in genetically edited loss-of-function (NRF2-/-) and disease-related gain-of-function (NRF2T80K and KEAP1-/-) cell-lines. Of the new partners investigated >77% (17/22) modified NRF2 responses, including partners that only exhibited effects under disease-related conditions. This experimentally defined binary NRF2 interactome provides a new vision of the complex molecular networks that govern the modulation and consequence of NRF2 activity in health and disease.

Parental age effects on neonatal white matter development.

OBJECTIVE: Advanced paternal age is associated with poor offspring developmental outcome. Though an increase in paternal age-related germline mutations may affect offspring white matter development, outcome differences could also be due to psychosocial factors. Here we investigate possible cerebral changes prior to strong environmental influences using brain MRI in a cohort of healthy term-born neonates. METHODS: We used structural and diffusion MRI images acquired soon after birth from a cohort (n = 275) of healthy term-born neonates. Images were analysed using a customised tract based spatial statistics (TBSS) processing pipeline. Neurodevelopmental assessment using the Bayley-III scales was offered to all participants at age 18 months. For statistical analysis neonates were compared in two groups, representing the upper quartile (paternal age ≥38 years) and lower three quartiles. The same method was used to assess associations with maternal age. RESULTS: In infants with older fathers (≥38 years), fractional anisotropy, a marker of white matter organisation, was significantly reduced in three early maturing anatomical locations (the corticospinal tract, the corpus callosum, and the optic radiation). Fractional anisotropy in these locations correlated positively with Bayley-III cognitive composite score at 18 months in the advanced paternal age group. A small but significant reduction in total brain volume was also observed in in the infants of older fathers. No significant associations were found between advanced maternal age and neonatal imaging. CONCLUSIONS: The epidemiological association between advanced paternal age and offspring outcome is extremely robust. We have for the first time demonstrated a neuroimaging phenotype of advanced paternal age before sustained parental interaction that correlates with later outcome.