Pediatric Device Clinical Trials Activity: 1999-2022.

OBJECTIVES: This study assessed the state of pediatric medical device (PMD) development by comparing PMD clinical trials to pediatric trials evaluating drugs and biologics, from 1999 to 2022. METHODS: The site www.clinicaltrials.gov was used to identify and quantify both PMD clinical trials and pediatric trials for drugs and biologics. Clinical specialty was also assessed. The institutions included were the 7 children's hospitals primarily affiliated with the Food and Drug Administration (FDA) Pediatric Device Consortia (PDC) grant program between 2018 and 2023. For a national comparison, an additional search assessed PMD trials across all US medical institutions. RESULTS: A total of 243 PMD clinical trials were identified at the FDA-PDC institutions on the basis of the year of initiation; the average number of PMD trials initiated per year per institution was 1.5 from 1999 to 2022. However, PMD trials significantly increased during the period 2014 to 2022 compared with 1999 to 2013 (P < .001); the rate of initiation of drug and biologic pediatric trials demonstrated no significant differences between these time periods. A national survey of all institutions initiating PMD trials, and drugs and biologics trials, identified 1885 PMD trials out of a total 12 943. A comparable trend was noted in the national survey with initiation of PMD trials increasing significantly from 2014 to 2022 (P < .001), compared with 1999 to 2013, whereas the rate of initiation of drug and biologic trials during these periods did not demonstrate a significant change. CONCLUSIONS: Although pediatric clinical trial initiation for drugs and biologics remained stable from 1999 to 2022, the rate of new PMD trials significantly increased during the period 2014 to 2022 at FDA-PDC institutions and nationally.

Sharing parental genomes by siblings concordant or discordant for autism.

Studying thousands of families, we find siblings concordant for autism share more of their parental genomes than expected by chance, and discordant siblings share less, consistent with a role of transmission in autism incidence. The excess sharing of the father is highly significant (p value of 0.0014), with less significance for the mother (p value of 0.31). To compare parental sharing, we adjust for differences in meiotic recombination to obtain a p value of 0.15 that they are shared equally. These observations are contrary to certain models in which the mother carries a greater load than the father. Nevertheless, we present models in which greater sharing of the father is observed even though the mother carries a greater load. More generally, our observations of sharing establish quantitative constraints that any complete genetic model of autism must satisfy, and our methods may be applicable to other complex disorders.

Decreased serotonin transporter activity in the mitral valve contributes to progression of degenerative mitral regurgitation.

Degenerative mitral valve (MV) regurgitation (MR) is a highly prevalent heart disease that requires surgery in severe cases. Here, we show that a decrease in the activity of the serotonin transporter (SERT) accelerates MV remodeling and progression to MR. Through studies of a population of patients with MR, we show that selective serotonin reuptake inhibitor (SSRI) use and SERT promoter polymorphism 5-HTTLPR LL genotype were associated with MV surgery at younger age. Functional characterization of 122 human MV samples, in conjunction with in vivo studies in SERT-/- mice and wild-type mice treated with the SSRI fluoxetine, showed that diminished SERT activity in MV interstitial cells (MVICs) contributed to the pathophysiology of MR through enhanced serotonin receptor (HTR) signaling. SERT activity was decreased in LL MVICs partially because of diminished membrane localization of SERT. In mice, fluoxetine treatment or SERT knockdown resulted in thickened MV leaflets. Similarly, silencing of SERT in normal human MVICs led to up-regulation of transforming growth factor ß1 (TGFß1) and collagen (COL1A1) in the presence of serotonin. In addition, treatment of MVICs with fluoxetine not only directly inhibited SERT activity but also decreased SERT expression and increased HTR2B expression. Fluoxetine treatment and LL genotype were also associated with increased COL1A1 expression in the presence of serotonin in MVICs, and these effects were attenuated by HTR2B inhibition. These results suggest that assessment of both 5-HTTLPR genotype and SERT-inhibiting treatments may be useful tools to risk-stratify patients with MV disease to estimate the likelihood of rapid disease progression.

Inhibition of advanced glycation end product formation and serum protein infiltration in bioprosthetic heart valve leaflets: Investigations of anti-glycation agents and anticalcification interactions with ethanol pretreatment.

Bioprosthetic heart valves (BHV) fabricated from heterograft tissue, such as glutaraldehyde pretreated bovine pericardium (BP), are the most frequently used heart valve replacements. BHV durability is limited by structural valve degeneration (SVD), mechanistically associated with calcification, advanced glycation end products (AGE), and serum protein infiltration. We investigated the hypothesis that anti-AGE agents, Aminoguanidine, Pyridoxamine [PYR], and N-Acetylcysteine could mitigate AGE-serum protein SVD mechanisms in vitro and in vivo, and that these agents could mitigate calcification or demonstrate anti-calcification interactions with BP pretreatment with ethanol. In vitro, each of these agents significantly inhibited AGE-serum protein infiltration in BP. However, in 28-day rat subdermal BP implants only orally administered PYR demonstrated significant inhibition of AGE and serum protein uptake. Furthermore, BP PYR preincubation of BP mitigated AGE-serum protein SVD mechanisms in vitro, and demonstrated mitigation of both AGE-serum protein uptake and reduced calcification in vivo in 28-day rat subdermal BP explants. Inhibition of BP calcification as well as inhibition of AGE-serum protein infiltration was observed in 28-day rat subdermal BP explants pretreated with ethanol followed by PYR preincubation. In conclusion, AGE-serum protein and calcification SVD pathophysiology are significantly mitigated by both PYR oral therapy and PYR and ethanol pretreatment of BP.

Poly-2-methyl-2-oxazoline-modified bioprosthetic heart valve leaflets have enhanced biocompatibility and resist structural degeneration.

Bioprosthetic heart valves (BHV) fabricated from glutaraldehyde-fixed heterograft tissue, such as bovine pericardium (BP), are widely used for treating heart valve disease, a group of disorders that affects millions. Structural valve degeneration (SVD) of BHV due to both calcification and the accumulation of advanced glycation end products (AGE) with associated serum proteins limits durability. We hypothesized that BP modified with poly-2-methyl-2-oxazoline (POZ) to inhibit protein entry would demonstrate reduced accumulation of AGE and serum proteins, mitigating SVD. In vitro studies of POZ-modified BP demonstrated reduced accumulation of serum albumin and AGE. BP-POZ in vitro maintained collagen microarchitecture per two-photon microscopy despite AGE incubation, and in cell culture studies was associated with no change in tumor necrosis factor-α after exposure to AGE and activated macrophages. Comparing POZ and polyethylene glycol (PEG)-modified BP in vitro, BP-POZ was minimally affected by oxidative conditions, whereas BP-PEG was susceptible to oxidative deterioration. In juvenile rat subdermal implants, BP-POZ demonstrated reduced AGE formation and serum albumin infiltration, while calcification was not inhibited. However, BP-POZ rat subdermal implants with ethanol pretreatment demonstrated inhibition of both AGE accumulation and calcification. Ex vivo laminar flow studies with human blood demonstrated BP-POZ enhanced thromboresistance with reduced white blood cell accumulation. We conclude that SVD associated with AGE and serum protein accumulation can be mitigated through POZ functionalization that both enhances biocompatibility and facilitates ethanol pretreatment inhibition of BP calcification.

Rates of contributory de novo mutation in high and low-risk autism families.

Autism arises in high and low-risk families. De novo mutation contributes to autism incidence in low-risk families as there is a higher incidence in the affected of the simplex families than in their unaffected siblings. But the extent of contribution in low-risk families cannot be determined solely from simplex families as they are a mixture of low and high-risk. The rate of de novo mutation in nearly pure populations of high-risk families, the multiplex families, has not previously been rigorously determined. Moreover, rates of de novo mutation have been underestimated from studies based on low resolution microarrays and whole exome sequencing. Here we report on findings from whole genome sequence (WGS) of both simplex families from the Simons Simplex Collection (SSC) and multiplex families from the Autism Genetic Resource Exchange (AGRE). After removing the multiplex samples with excessive cell-line genetic drift, we find that the contribution of de novo mutation in multiplex is significantly smaller than the contribution in simplex. We use WGS to provide high resolution CNV profiles and to analyze more than coding regions, and revise upward the rate in simplex autism due to an excess of de novo events targeting introns. Based on this study, we now estimate that de novo events contribute to 52-67% of cases of autism arising from low risk families, and 30-39% of cases of all autism.

Model studies of advanced glycation end product modification of heterograft biomaterials: The effects of in vitro glucose, glyoxal, and serum albumin on collagen structure and mechanical properties.

Glutaraldehyde cross-linked heterograft tissues, bovine pericardium (BP) or porcine aortic valves, are the leaflet materials in bioprosthetic heart valves (BHV) used in cardiac surgery for heart valve disease. BHV fail due to structural valve degeneration (SVD), often with calcification. Advanced glycation end products (AGE) are post-translational, non-enzymatic reaction products from sugars reducing proteins. AGE are present in SVD-BHV clinical explants and are not detectable in un-implanted BHV. Prior studies modeled BP-AGE formation in vitro with glyoxal, a glucose breakdown product, and serum albumin. However, glucose is the most abundant AGE precursor. Thus, the present studies investigated the hypothesis that BHV susceptibility to glucose related AGE, together with serum proteins, results in deterioration of collagen structure and mechanical properties. In vitro experiments studied AGE formation in BP and porcine collagen sponges (CS) comparing 14C-glucose and 14C-glyoxal with and without bovine serum albumin (BSA). Glucose incorporation occurred at a significantly lower level than glyoxal (p<0.02). BSA co-incubations demonstrated reduced glyoxal and glucose uptake by both BP and CS. BSA incubation caused a significant increase in BP mass, enhanced by glyoxal co-incubation. Two-photon microscopy of BP showed BSA induced disruption of collagen structure that was more severe with glucose or glyoxal co-incubation. Uniaxial testing of CS demonstrated that glucose or glyoxal together with BSA compared to controls, caused accelerated deterioration of viscoelastic relaxation, and increased stiffness over a 28-day time course. In conclusion, glucose, glyoxal and BSA uniquely contribute to AGE-mediated disruption of heterograft collagen structure and deterioration of mechanical properties.

Electrocorticography reveals spatiotemporal neuronal activation patterns of verbal fluency in patients with epilepsy.

Verbal fluency is commonly used to evaluate cognitive dysfunction in a variety of neuropsychiatric diseases, yet the neurobiology underlying performance of this task is incompletely understood. Electrocorticography (ECoG) provides a unique opportunity to investigate temporal activation patterns during cognitive tasks with high spatial and temporal precision. We used ECoG to study high gamma activity (HGA) patterns in patients undergoing presurgical evaluation for intractable epilepsy as they completed an overt, free-recall verbal fluency task. We examined regions demonstrating changes in HGA during specific timeframes relative to speech onset. Early pre-speech high gamma activity was present in left frontal regions during letter fluency and in bifrontal regions during category fluency. During timeframes typically associated with word planning, a distributed network was engaged including left inferior frontal, orbitofrontal and posterior temporal regions. Peri-Rolandic activation was observed during speech onset, and there was post-speech activation in the bilateral posterior superior temporal regions. Based on these observations in the context of prior studies, we propose a model of neocortical activity patterns underlying verbal fluency.

Damaging de novo mutations diminish motor skills in children on the autism spectrum.

In individuals with autism spectrum disorder (ASD), de novo mutations have previously been shown to be significantly correlated with lower IQ but not with the core characteristics of ASD: deficits in social communication and interaction and restricted interests and repetitive patterns of behavior. We extend these findings by demonstrating in the Simons Simplex Collection that damaging de novo mutations in ASD individuals are also significantly and convincingly correlated with measures of impaired motor skills. This correlation is not explained by a correlation between IQ and motor skills. We find that IQ and motor skills are distinctly associated with damaging mutations and, in particular, that motor skills are a more sensitive indicator of mutational severity than is IQ, as judged by mutational type and target gene. We use this finding to propose a combined classification of phenotypic severity: mild (little impairment of either), moderate (impairment mainly to motor skills), and severe (impairment of both IQ and motor skills).

Intracranial EEG fluctuates over months after implanting electrodes in human brain.

OBJECTIVE: Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. APPROACH: Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient's recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. MAIN RESULTS: A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. SIGNIFICANCE: These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Measuring shared variants in cohorts of discordant siblings with applications to autism.

We develop a method of analysis [affected to discordant sibling pairs (A2DS)] that tests if shared variants contribute to a disorder. Using a standard measure of genetic relation, test individuals are compared with a cohort of discordant sibling pairs (CDS) to derive a comparative similarity score. We ask if a test individual is more similar to an unrelated affected than to the unrelated unaffected sibling from the CDS and then, sum over such individuals and pairs. Statistical significance is judged by randomly permuting the affected status in the CDS. In the analysis of published genotype data from the Simons Simplex Collection (SSC) and the Autism Genetic Resource Exchange (AGRE) cohorts of children with autism spectrum disorder (ASD), we find strong statistical significance that the affected are more similar to the affected than to the unaffected of the CDS (P value ∼ 0.00001). Fathers in multiplex families have marginally greater similarity (P value = 0.02) to unrelated affected individuals. These results do not depend on ethnic matching or gender.

Dosage-dependent phenotypes in models of 16p11.2 lesions found in autism.

Recurrent copy number variations (CNVs) of human 16p11.2 have been associated with a variety of developmental/neurocognitive syndromes. In particular, deletion of 16p11.2 is found in patients with autism, developmental delay, and obesity. Patients with deletions or duplications have a wide range of clinical features, and siblings carrying the same deletion often have diverse symptoms. To study the consequence of 16p11.2 CNVs in a systematic manner, we used chromosome engineering to generate mice harboring deletion of the chromosomal region corresponding to 16p11.2, as well as mice harboring the reciprocal duplication. These 16p11.2 CNV models have dosage-dependent changes in gene expression, viability, brain architecture, and behavior. For each phenotype, the consequence of the deletion is more severe than that of the duplication. Of particular note is that half of the 16p11.2 deletion mice die postnatally; those that survive to adulthood are healthy and fertile, but have alterations in the hypothalamus and exhibit a "behavior trap" phenotype-a specific behavior characteristic of rodents with lateral hypothalamic and nigrostriatal lesions. These findings indicate that 16p11.2 CNVs cause brain and behavioral anomalies, providing insight into human neurodevelopmental disorders.

Neutral mitochondrial heteroplasmy and the influence of aging.

The development and maintenance of mitochondrial heteroplasmy has important consequences for both health and heredity. Previous studies using pathogenic mutations have shown considerable variability between maternally related individuals and studies of several D-loop polymorphisms have suggested a relationship between heteroplasmy and somatic aging. To broadly explore the variation of human heteroplasmy and to clarify the dynamics of somatic heteroplasmy over the course of lifespan, we analyzed mitochondrial sequence variation across a range of ages. We utilized array-generated single-nucleotide polymorphism data that were well correlated with independent measures of heteroplasmy. Significant levels of heteroplasmy were identified at 0.24% of sites evaluated. By examining mother-child pairs, we found that heteroplasmy was inherited (30%) but could occur de novo in offspring or, conversely, be present in mothers but eliminated in their children (70%). Cumulatively, mitochondrial heteroplasmy across the genome increased significantly with advanced age (r = 0.224, P =8 × 10(-30)). Surprisingly, changes in heteroplasmy were not uniform with some sites demonstrating a loss of variation (increased homoplasmy) with aging. These data suggest that both mutation and selective pressure affect blood mitochondrial DNA sequence over the course of the human lifespan and reveal the unexpectedly dynamic nature of human heteroplasmy.

Early biometric lag in the prediction of small for gestational age neonates and preeclampsia.

OBJECTIVE: An early fetal growth lag may be a marker of future complications. We sought to determine the utility of early biometric variables in predicting adverse pregnancy outcomes. METHODS: In this retrospective cohort study, the crown-rump length at 11 to 14 weeks and the head circumference, biparietal diameter, abdominal circumference, femur length, humerus length, transverse cerebellar diameter, and estimated fetal weight at 18 to 24 weeks were converted to an estimated gestational age using published regression formulas. Sonographic fetal growth (difference between each biometric gestational age and the crown-rump length gestational age) minus expected fetal growth (number of days elapsed between the two scans) yielded the biometric growth lag. These lags were tested as predictors of small for gestational age (SGA) neonates (≤10th percentile) and preeclampsia. RESULTS: A total of 245 patients were included. Thirty-two (13.1%) delivered an SGA neonate, and 43 (17.6%) had the composite outcome. The head circumference, biparietal diameter, abdominal circumference, and estimated fetal weight lags were identified as significant predictors of SGA neonates after adjusted analyses (P < .05). The addition of either the estimated fetal weight or abdominal circumference lag to maternal characteristics alone significantly improved the performance of the predictive model, achieving areas under the curve of 0.72 and 0.74, respectively. No significant association was found between the biometric lag variables and the development of preeclampsia. CONCLUSIONS: Routinely available biometric data can be used to improve the prediction of adverse outcomes such as SGA. These biometric lags should be considered in efforts to develop screening algorithms for adverse outcomes.

A stochastic framework for evaluating seizure prediction algorithms using hidden Markov models.

Responsive, implantable stimulation devices to treat epilepsy are now in clinical trials. New evidence suggests that these devices may be more effective when they deliver therapy before seizure onset. Despite years of effort, prospective seizure prediction, which could improve device performance, remains elusive. In large part, this is explained by lack of agreement on a statistical framework for modeling seizure generation and a method for validating algorithm performance. We present a novel stochastic framework based on a three-state hidden Markov model (HMM) (representing interictal, preictal, and seizure states) with the feature that periods of increased seizure probability can transition back to the interictal state. This notion reflects clinical experience and may enhance interpretation of published seizure prediction studies. Our model accommodates clipped EEG segments and formalizes intuitive notions regarding statistical validation. We derive equations for type I and type II errors as a function of the number of seizures, duration of interictal data, and prediction horizon length and we demonstrate the model's utility with a novel seizure detection algorithm that appeared to predicted seizure onset. We propose this framework as a vital tool for designing and validating prediction algorithms and for facilitating collaborative research in this area.

Causal conclusions are most sensitive to unobserved binary covariates.

There is a rich literature that considers whether an observed relation between treatment and response is due to an unobserved covariate. In order to quantify this unmeasured bias, an assumption is made about the distribution of this unobserved covariate; typically that it is either binary or at least confined to the unit interval. In this paper, this assumption is relaxed in the context of matched pairs with binary treatment and response. One might think that a long-tailed unobserved covariate could do more damage. Remarkably that is not the case: the most harm is done by a binary covariate, so the case commonly considered in the literature is most conservative. This has two practical consequences: (i) it is always safe to assume that an unobserved covariate is binary, if one is content to make a conservative statement; (ii) when another assumption seems more appropriate, say normal covariate, there will be less sensitivity than with a binary covariate. This assumption implies that it is possible that a relation between treatment and response that is sensitive to unmeasured bias (if the unobserved covariate is dichotomous), ceases to be sensitive if the unobserved covariate is normally distributed. These ideas are illustrated by three examples. It is important to note that the claim in this paper applies to our specific setting of matched pairs with binary treatment and response. Whether the same conclusion holds in other settings is an open question.