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Abstract Purpose To compare ovulation rates between Letrozole and Clomiphene Citrate (CC) using a stair-step protocol to achieve ovulation induction in women with Polycystic Ovarian Syndrome (PCOS). Methods This is a retrospective cohort of predominantly Hispanic PCOS women of reproductive age who completed ovulation induction (OI) comparing women who underwent Letrozole stair-step protocol to those who underwent OI with CC stair-step. All women had a diagnosis of PCOS based on the 2003 Rotterdam criteria. For both protocols, sequentially higher doses of Letrozole or CC were given 7 days after the last dose if no dominant follicles were seen on ultrasonography. The primary outcome was ovulation rate (determined by presence of a dominant follicle) between the two treatment groups. Secondary outcomes included time to ovulation, clinical pregnancy rates and side effects. Results 49 PCOS patients completed a Letrozole stair-step cycle and 43 completed a CC stair-step cycle for OI. Overall, demographics were comparable between both groups. Ovulation rates with the Letrozole stair-step protocol were equivalent to CC stair-step protocol (96% vs 88%, p = 0.17). Although the mean time (days) to ovulation was shorter in the Letrozole group (19.5 vs 23.1, p = 0.027), the pregnancy rates were similar for both groups. Conclusions This is the first study to date that has compared the efficacy of the stair-step protocol in PCOS patients using Letrozole and CC. Both Letrozole and CC can be prescribed in a stair-step fashion. Letrozole stair-step was as efficacious as CC stair-step; patients achieved comparable rates of ovulation and clinical pregnancy. Time to ovulation was shorter in the Letrozole protocol.

Introduction Incidence for depression increases during the perinatal period. Risk factors for depression may differentially affect each time period. Objectives To assess demographic, psychological and obstetric risk factors that differentially affect prenatal and postpartum depression Methods A total of 169 subjects participated. Assessment was conducted during the first trimester, second trimester, third trimester, within a month after childbirth, and a month after childbirth. Demographic and obstetric measures, as well as psychological measures, including the Edinburgh Postnatal Depression Scale were conducted. Multiple regression and the Mann-Whitney U test were performed to examine the association between variables and depression scores. Results Depression score was higher during the postpartum period than the prenatal period. Younger age was associated with depression during the first trimester. In the second trimester, less education, a history of depression and having stress within a year significantly affected depression scores. Smoking, artificial abortion and lack of support from family and parents correlated with depression during the third trimester. Within a month after childbirth, psychiatric and depression history, smoking, stress level within a year and lack of family support were associated with depression. At a month after childbirth, those who were primiparous and not breastfeeding had significantly higher depression scores. Conclusions This study identifies various risk factors for each gestational and postpartum period and suggests differential interventions for different perinatal periods.

Abstract The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare (

Autism is heterogeneous at many levels, including clinical symptoms and etiology. A key strategy in studying heterogeneous conditions is having large enough sample sizes to stratify into smaller groups that are more homogeneous. SPARK and Simons Searchlight are large and growing research cohorts of individuals with autism in the United States and individuals with genetically defined neurodevelopmental conditions around the world, respectively. They both provide freely available phenotypic and genotypic data with the ability to re-contact participants through the research match program. Deep dives into each gene in Searchlight provide comprehensive natural history data to understand the differing clinical courses to inform proper clinical care, and work toward treatment for each condition. Moreover, pilots of genetically based newborn screening programs for neurogenetic disorders can provide opportunities for equitable and early diagnosis to try to improve outcomes with earlier interventions.

Abstract Background Optimizing resuscitation to reduce inflammation and organ dysfunction following human trauma-associated hemorrhagic shock is a major clinical hurdle. This is limited by the short duration of pre-clinical studies and the sparsity of early data in the clinical setting. Methods We sought to bridge this gap by linking preclinical data in a porcine model with clinical data from patients from the Prospective, Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a three-compartment ordinary differential equation model of inflammation and coagulation. Results The mathematical model accurately predicts physiologic, inflammatory, and laboratory measures in both the porcine model and patients, as well as the outcome and time of death in the PROMMTT cohort. Model simulation suggests that resuscitation with plasma and red blood cells outperformed resuscitation with crystalloid or plasma alone, and that earlier plasma resuscitation reduced injury severity and increased survival time. Conclusions This workflow may serve as a translational bridge from pre-clinical to clinical studies in trauma-associated hemorrhagic shock and other complex disease settings.

Summary: Background: NOTCH3 encodes a transmembrane receptor critical for vascular smooth muscle cell function. NOTCH3 variants are the leading cause of hereditary cerebral small vessel disease (SVD). While monoallelic cysteine-involving missense variants in NOTCH3 are well-studied in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), patients with biallelic variants in NOTCH3 are extremely rare and not well characterised. Methods: In this study, we present clinical and genetic data from 25 patients with biallelic NOTCH3 variants and conduct a literature review of another 25 cases (50 patients in total). Brain magnetic resonance imaging (MRI) were analysed by expert neuroradiologists to better understand the phenotype associated with biallelic NOTCH3 variants. Findings: Our systematic analyses verified distinct genotype-phenotype correlations for the two types of biallelic variants in NOTCH3. Biallelic loss-of-function variants (26 patients) lead to a neurodevelopmental disorder characterised by spasticity, childhood-onset stroke, and periatrial white matter volume loss resembling periventricular leukomalacia. Conversely, patients with biallelic cysteine-involving missense variants (24 patients) fall within CADASIL spectrum phenotype with early adulthood onset stroke, dementia, and deep white matter lesions without significant volume loss. White matter lesion volume is comparable between patients with biallelic cysteine-involving missense variants and individuals with CADASIL. Notably, monoallelic carriers of loss-of-function variants are predominantly asymptomatic, with only a few cases reporting nonspecific headaches. Interpretation: We propose a NOTCH3-SVD classification depending on dosage and variant type. This study not only expands our knowledge of biallelic NOTCH3 variants but also provides valuable insight into the underlying mechanisms of the disease, contributing to a more comprehensive understanding of NOTCH3-related SVD. Funding: The Wellcome Trust, the MRC.

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

As mortality relating to severe acute burn injury improves, patients are surviving longer into the critical care phase, which is commonly complicated by multisystem organ failure. Extracorporeal organ support (ECOS) represents a set of potential therapeutic technologies for managing patients with organ-specific complications. This article provides a comprehensive review of the existing literature, focusing on the use of continuous kidney replacement therapy, extracorporeal membrane oxygenation, extracorporeal carbon dioxide removal, and extracorporeal blood purification. Though promising, many of these technologies are in the early phases of implementation and are restricted to well-resourced medical systems, limiting their use in large scale casualty and austere scenarios.

Abstract Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinically-estimated risk of rupture—an event that is the 13th leading cause of death in the US—exceeds the risk associated with repair. Yet the current clinical guideline remains a one-size-fits-all “maximum diameter criterion” whereby AAA exceeding a threshold diameter is thought to make the risk of rupture high enough to warrant intervention. However, between 7 and 23.4% of smaller-sized AAA have been reported to rupture with diameters below the threshold. In this study, we train and assess machine learning models using clinical, biomechanical, and morphological indices from 381 patients to develop an aneurysm prognosis classifier to predict one of three outcomes for a given AAA patient: their AAA will remain stable, their AAA will require repair based as currently indicated from the maximum diameter criterion, or their AAA will rupture. This study represents the largest cohort of AAA patients that utilizes the first available medical image and clinical data to classify patient outcomes. The APC model therefore represents a potential clinical tool to striate specific patient outcomes using machine learning models and patient-specific image-based (biomechanical and morphological) and clinical data as input. Such a tool could greatly assist clinicians in their management decisions for patients with AAA.

Abstract Background Protein phosphatase 2 regulatory subunit B’ Delta (PPP2R5D)-related neurodevelopmental disorder is a rare genetic condition caused by pathogenic variants in the PPP2R5D gene. Clinical signs include hypotonia, gross motor delay, intellectual disability (ID), epilepsy, speech delays, and abnormal gait among other impairments. As this disorder was recognized within the last decade, there are only 103 people published diagnoses to date. A thorough understanding of the motor manifestations of this disorder has not yet been established. Knowledge of the natural history of PPP2R5D related neurodevelopmental disorder will lead to improved standard of care treatments as well as serve as a baseline foundation for future clinical trials. Appropriate outcome measures are necessary for use in clinical trials to uniformly measure function and monitor potential for change. The aim of this study was to validate the gross motor function measure (GMFM) in children and adults with PPP2R5D-related neurodevelopmental disorder in order to better characterize the disorder. Results Thirty-eight individuals with PPP2R5D pathogenic variants, median age 8.0 years (range 1–27) were evaluated. Gross motor, upper limb and ambulatory function were assessed using the GMFM-66, six-minute walk test (6MWT), 10-meter walk run (10MWR), timed up and go (TUG), and revised upper limb module (RULM). The pediatric disability inventory computer adapted test (PEDI-CAT) captured caregiver reported assessment. Median GMFM-66 score was 60.6 (SD = 17.3, range 21.1–96.0). There were strong associations between the GMFM-66 and related mobility measures, 10MWR (rs = −0.733; p < 0.001), TUG (rs= −0.747; p = 0.003), 6MWT (r = 0.633; p = 0.006), RULM (r = 0.763; p < 0.001), PEDICAT-mobility (r = 0.855; p < 0.001), and daily activities (r = 0.822; p < 0.001) domains. Conclusions The GMFM is a valid measure for characterizing motor function in individuals with PPP2R5D related neurodevelopmental disorder. The GMFM-66 had strong associations with the RULM and timed function tests which characterized gross motor, upper limb and ambulatory function demonstrating concurrent validity. The GMFM-66 was also able to differentiate between functional levels in PPP2R5D related neurodevelopmental disorder demonstrating discriminant validity. Future studies should examine its sensitivity to change over time, ability to identify sub-phenotypes, and suitability as an outcome measure in future clinical trials in individuals with PPP2R5D variants.

Abstract Objective Persons with congenital heart disease (CHD) are at increased risk of neurodevelopmental disabilities, including impairments to executive function. Sulcal pattern features correlate with executive function in adolescents with single‐ventricle heart disease and tetralogy of Fallot. However, the interaction of sulcal pattern features with genetic and participant factors in predicting executive dysfunction is unknown. Methods We studied sulcal pattern features, participant factors, and genetic risk for executive function impairment in a cohort with multiple CHD types using stepwise linear regression and machine learning. Results Genetic factors, including predicted damaging de novo or rare inherited variants in neurodevelopmental disabilities risk genes, apolipoprotein E genotype, and principal components of sulcal pattern features were associated with executive function measures after adjusting for age at testing, sex, mother's education, and biventricular versus single‐ventricle CHD in a linear regression model. Using regression trees and bootstrap validation, younger participant age and larger alterations in sulcal pattern features were consistently identified as important predictors of decreased cognitive flexibility with left hemisphere graph topology often selected as the most important predictor. Inclusion of both sulcal pattern and genetic factors improved model fit compared to either alone. Interpretation We conclude that sulcal measures remain important predictors of cognitive flexibility, and the model predicting executive outcomes is improved by inclusion of potential genetic sources of neurodevelopmental risk. If confirmed, measures of sulcal patterning may serve as early imaging biomarkers to identify those at heightened risk for future neurodevelopmental disabilities.

Topological data analysis (TDA) is increasingly recognized as a promising tool in the field of neuroscience, unveiling the underlying topological patterns within brain signals. However, most TDA related methods treat brain signals as if they were static, i.e., they ignore potential non-stationarities and irregularities in the statistical properties of the signals. In this study, we develop a novel fractal dimension-based testing approach that takes into account the dynamic topological properties of brain signals. By representing EEG brain signals as a sequence of Vietoris-Rips filtrations, our approach accommodates the inherent non-stationarities and irregularities of the signals. The application of our novel fractal dimension-based testing approach in analyzing dynamic topological patterns in EEG signals during an epileptic seizure episode exposes noteworthy alterations in total persistence across 0, 1, and 2-dimensional homology. These findings imply a more intricate influence of seizures on brain signals, extending beyond mere amplitude changes.

A stable, minimum physiological health status is required for patients to qualify for transplant or artificial organ support eligibility to ensure the recipient has enough reserve to survive the perioperative transplant period. Herein, we present a novel strategy to stabilize and improve patient clinical status through extracorporeal immunomodulation of systemic hyperinflammation with impact on multiple organ systems to increase eligibility and feasibility for transplant/device implantation. This involves treatment with the selective cytopheretic device (SCD), a cell-directed extracorporeal therapy shown to adhere and immunomodulate activated neutrophils and monocytes toward resolution of systemic inflammation. In this overview, we describe a case series of successful transition of pediatric and adult patients with multiorgan failure to successful transplant/device implantation procedures by treatment with the SCD in the following clinical situations: pediatric hemophagocytic lymphohistiocytosis, and adult hepatorenal and cardiorenal syndromes. Application of the SCD in these cases may represent a novel paradigm in increasing clinical eligibility of patients to successful transplant outcomes.

We introduce an innovative, data-driven topological data analysis (TDA) technique for estimating the state spaces of dynamically changing functional human brain networks at rest. Our method utilizes the Wasserstein distance to measure topological differences, enabling the clustering of brain networks into distinct topological states. This technique outperforms the commonly used k-means clustering in identifying brain network state spaces by effectively incorporating the temporal dynamics of the data without the need for explicit model specification. We further investigate the genetic underpinnings of these topological features using a twin study design, examining the heritability of such state changes. Our findings suggest that the topology of brain networks, particularly in their dynamic state changes, may hold significant hidden genetic information.

Abstract African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1-associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Abstract Background Biallelic variants in OGDHL, encoding part of the α-ketoglutarate dehydrogenase complex, have been associated with highly heterogeneous neurological and neurodevelopmental disorders. However, the validity of this association remains to be confirmed. A second OGDHL patient cohort was recruited to carefully assess the gene-disease relationship. Methods Using an unbiased genotype-first approach, we screened large, multiethnic aggregated sequencing datasets worldwide for biallelic OGDHL variants. We used CRISPR/Cas9 to generate zebrafish knockouts of ogdhl, ogdh paralogs, and dhtkd1 to investigate functional relationships and impact during development. Functional complementation with patient variant transcripts was conducted to systematically assess protein functionality as a readout for pathogenicity. Results A cohort of 14 individuals from 12 unrelated families exhibited highly variable clinical phenotypes, with the majority of them presenting at least one additional variant, potentially accounting for a blended phenotype and complicating phenotypic understanding. We also uncovered extreme clinical heterogeneity and high allele frequencies, occasionally incompatible with a fully penetrant recessive disorder. Human cDNA of previously described and new variants were tested in an ogdhl zebrafish knockout model, adding functional evidence for variant reclassification. We disclosed evidence of hypomorphic alleles as well as a loss-of-function variant without deleterious effects in zebrafish variant testing also showing discordant familial segregation, challenging the relationship of OGDHL as a conventional Mendelian gene. Going further, we uncovered evidence for a complex compensatory relationship among OGDH, OGDHL, and DHTKD1 isoenzymes that are associated with neurodevelopmental disorders and exhibit complex transcriptional compensation patterns with partial functional redundancy. Conclusions Based on the results of genetic, clinical, and functional studies, we formed three hypotheses in which to frame observations: biallelic OGDHL variants lead to a highly variable monogenic disorder, variants in OGDHL are following a complex pattern of inheritance, or they may not be causative at all. Our study further highlights the continuing challenges of assessing the validity of reported disease-gene associations and effects of variants identified in these genes. This is particularly more complicated in making genetic diagnoses based on identification of variants in genes presenting a highly heterogenous phenotype such as “OGDHL-related disorders”.

Genome-wide association studies have identified a locus on chromosome 10q22, where many co-inherited single nucleotide polymorphisms (SNPs) are associated with atrial fibrillation (AF). This study seeks to identify the impact of this locus on gene expression at the transcript isoform level in human left atria and to gain insight into potential causal variants. Bulk RNA sequencing was analyzed to identify myozenin 1 (MYOZ1) and synaptopodin 2-like (SYNPO2L) transcript isoforms and the association of common SNPs in this region with transcript isoform expression levels. Chromatin marks were used to suggest candidate regulatory SNPs in this region. Protein amino acid changes were examined for predicted functional consequences. Transfection of MYOZ1 and two SYNPO2L isoforms were performed to localize their encoded proteins in cardiomyocytes derived from stem cells. We identified one MYOZ1 transcript isoform and four SYNPO2L transcript isoforms, two of which encode proteins, while the other two encode long noncoding RNAs (lncRNAs). The risk allele of the strongest AF susceptibility SNP on chromosome 10q22 is associated with decreased MYOZ1 expression and increased expression of the two SNYPO2L lncRNA isoforms. There are many SNPs co-inherited with the top AF-associated SNP due to linkage disequilibrium (LD), including rs11000728, which we propose as the MYOZ1 regulatory SNP, confirmed by reporter gene transfection. In addition, this LD block includes three missense SNPs in the SYNPO2L gene, with the minor protective haplotype predicted to be detrimental to protein function. MYOZ1 and both protein isoforms of SYNPO2L were localized to the sarcomere. This is a complex locus with the potential for several SNPs in a haplotype to alter AF susceptibility by opposing effects on MYOZ1 and SYNPO2L lncRNA expression, along with effects on SYNPO2L protein function.

This study aimed to develop and validate a new measurement tool, the Rehabilitation Adherence Inventory (RAI), to measure patients’ rehabilitation adherence. We recruited 236 patients with anterior cruciate ligament (ACL) ruptures from the United Kingdom (Mage = 33.58 ± 10.03, range = 18 to 59; female = 46.2%). Participants completed a survey, that measured their rehabilitation adherence, rehabilitation volume, psychological needs support, autonomous motivation, and intention at baseline, and at the 2nd and 4th month. Factorial, convergent, discriminant, concurrent, predictive, ecological validity and test–retest reliability of the RAI were tested via exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modelling (SEM). All the EFAs, CFAs, and SEMs yielded acceptable to excellent goodness-of-fit, χ2 = 10.51 to 224.12, df = 9 to 161, CFI > 0.95, TLI > 0.95, RMSEA

Summary: Research on polygenic risk scores (PRSs) for common, genetically complex chronic diseases aims to improve health-related predictions, tailor risk-reducing interventions, and improve health outcomes. Yet, the study and use of PRSs in clinical settings raise equity, clinical, and regulatory challenges that can be greater for individuals from historically marginalized racial, ethnic, and other minoritized communities. As part of the National Human Genome Research Institute-funded Electronic Medical Records and Genomics IV Network, we conducted online focus groups with patients/community members, clinicians, and members of institutional review boards to explore their views on key issues, including PRS research, return of PRS results, clinical translation, and barriers and facilitators to health behavioral changes in response to PRS results. Across stakeholder groups, our findings indicate support for PRS development and a strong interest in having PRS results returned to research participants. However, we also found multi-level barriers and significant differences in stakeholders’ views about what is needed and possible for successful implementation. These include researcher-participant interaction formats, health and genomic literacy, and a range of structural barriers, such as financial instability, insurance coverage, and the absence of health-supporting infrastructure and affordable healthy food options in poorer neighborhoods. Our findings highlight the need to revisit and implement measures in PRS studies (e.g., incentives and resources for follow-up care), as well as system-level policies to promote equity in genomic research and health outcomes.

IntroductionMultimodal evidence indicates Alzheimer’s disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes.Materials and methodsParticipants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics.ResultsBoth amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals’ brain graphs.DiscussionWe have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.

Summary: Background: Although immunomodulators have established benefit against the new coronavirus disease (COVID-19) in general, it is uncertain whether such agents improve outcomes without increasing the risk of secondary infections in the specific subgroup of previously immunocompromised patients. We assessed the effect of immunomodulators on outcomes of immunocompromised patients hospitalized for COVID-19. Methods: The protocol was prospectively registered with PROSPERO (CRD42022335397). MEDLINE, Cochrane Central Register of Controlled Trials and references of relevant articles were searched up to 01-06-2022. Authors of potentially eligible randomized controlled trials were contacted to provide data on immunocompromised patients randomized to immunomodulators vs control (i.e., placebo or standard-of-care). Findings: Eleven randomized controlled trials involving 397 immunocompromised patients hospitalized for COVID-19 were included. Ten trials had low risk of bias. There was no difference between immunocompromised patients randomized to immunomodulators vs control regarding mortality [30/182 (16.5%) vs 41/215 (19.1%); RR 0.93, 95% CI 0.61–1.41; p = 0.74], secondary infections (RR 1.00, 95% CI 0.64–1.58; p = 0.99) and change in World Health Organization ordinal scale from baseline to day 15 (weighed mean difference 0.27, 95% CI -0.09–0.63; p = 0.15). In subgroup analyses including only patients with hematologic malignancy, only trials with low risk of bias, only trials administering IL-6 inhibitors, or only trials administering immunosuppressants, there was no difference between comparators regarding mortality. Interpretation: Immunomodulators, compared to control, were not associated with harmful or beneficial outcomes, including mortality, secondary infections, and change in ordinal scale, when administered to immunocompromised patients hospitalized for COVID-19. Funding: Hellenic Foundation for Research and Innovation.

Abstract Background: The COVID-19 pandemic amplified known challenges associated with the conduct of inpatient clinical trials, while also introducing new ones that needed to be addressed. Methods: Stakeholders based in the United States who participated in the conduct of inpatient therapeutic trials for the treatment of COVID-19 as part of the Accelerating COVID-19 Therapeutic Interventions and Vaccines program identified challenges experienced in the conduct of these trials through a series of meeting to discuss and identify common themes. In addition, innovations developed to address these challenges and other potential solutions that may be utilized in future pandemics were highlighted. Results: Six thematic challenges including infection control considerations, the interplay between provision of clinical care and research, competing clinical trials, arduous consenting procedures, onerous procedural requirements, and participant recruitment including achieving representation of diverse populations were identified and are discussed here. Conclusions: Consideration of the lessons learned and recommendation outlined here may allow for more efficient conduct of inpatient clinical trials in future pandemics.

The United States Government (USG) public-private partnership “Accelerating COVID-19 Treatment Interventions and Vaccines” (ACTIV) was launched to identify safe, effective therapeutics to treat patients with Coronavirus Disease 2019 (COVID-19) and prevent hospitalization, progression of disease, and death. Eleven original master protocols were developed by ACTIV, and thirty-seven therapeutic agents entered evaluation for treatment benefit. Challenges encountered during trial implementation led to innovations enabling initiation and enrollment of over 26,000 participants in the trials. While only two ACTIV trials continue to enroll, the recommendations here reflect information from all the trials as of May 2023. We review clinical trial implementation challenges and corresponding lessons learned to inform future therapeutic clinical trials implemented in response to a public health emergency and the conduct of complex clinical trials during “peacetime,” as well.

Purpose: Limited knowledge about disease mechanisms, few published cases, and the lack of functional assessment of variants for neurodevelopmental genetic disorders challenge diagnostic classification for variants and increase the frequency of variants of uncertain significance (VUS). Because inheritance patterns aid in variant interpretation for neurodevelopmental conditions, genetic testing including only the proband leads to larger numbers of VUS than testing strategies that include the parents. Methods: We reinterpreted genetic variants submitted to the Simons Searchlight research registry using American College of Medical Genetics and Genomics variant interpretation guidelines, familial cascade testing, and literature curation with annual VUS reevaluation. Results: Simons Searchlight has independently evaluated 2834 genetic laboratory reports; 20.4% of variants (1.7% copy-number variants and 18.7% monogenic variants) were reclassified with 230 upgrades and 173 downgrades in pathogenicity. Of 351 monogenic VUS on the original clinical test report, 25.4% were reclassified as likely pathogenic or pathogenic. VUS in SCN2A, SLC6A1, or STXBP1 were more likely to have VUS reclassified compared with variants in other genes. Conclusion: Regular reevaluation of neurodevelopmental genetic variants can be helpful because relevant variant reclassifications occur frequently and may affect clinical care. Simons Searchlight contributes to the international neurodevelopmental community by systematically reviewing uncertain variants annually and providing reclassified variants to participants, researchers, and ClinVar.

Abstract Introduction: Under enrollment of participants in clinical research is costly and delays study completion to impact public health. Given that research personnel make decisions about which strategies to pursue and participants are the recipients of these efforts, we surveyed research staff (n = 52) and participants (n = 4,144) affiliated with SPARK (Simons Foundation Powering Autism for Knowledge) – the largest study of autism in the U.S. – to understand their perceptions of effective recruitment strategies. Methods: In Study 1, research personnel were asked to report recruitment strategies that they tried for SPARK and to indicate which ones they would and would not repeat/recommend. In Study 2, SPARK participants were asked to indicate all the ways they heard about the study prior to enrollment and which one was most influential in their decisions to enroll. Results: Staff rated speaking with a SPARK-study-team member (36.5%), speaking with a medical provider (19.2%), word of mouth (11.5%), and a live TV news story (11.5%) as the most successful strategies. Participants most often heard about SPARK via social media (47.0%), speaking with a medical provider (23.1%), and an online search (20.1%). Research personnel’s and participants’ views on effective recruitment strategies often differed, with the exception of speaking with a medical provider. Conclusion: Results suggest that a combination of strategies is likely to be most effective in reaching diverse audiences. Findings have implications for the selection of strategies that meet a study’s specific needs, as well as recruitment-strategy “combinations” that may enhance the influence of outreach efforts.

Abstract Background: SPARK launched in 2016 to build a US cohort of autistic individuals and their family members. Enrollment includes online consent to share data and optional consent to provide saliva for genomic analysis. SPARK’s recruitment strategies include social media and support of a nation-wide network of clinical sites. This study evaluates SPARK’s recruitment strategies to enroll a core study population. Methods: Individuals who joined between January 31, 2018, and May 29, 2019 were included in the analysis. Data include sociodemographic characteristics, clinical site referral, the website URL used to join, how the participant heard about SPARK, enrollment completion (online registration, study consents, and returning saliva sample), and completion of the baseline questionnaire. Logistic regressions were performed to evaluate the odds of core participant status (completing enrollment and baseline questionnaire) by recruitment strategy. Results: In total, 31,715 individuals joined during the study period, including 40% through a clinical site. Overall, 88% completed online registration, 46% returned saliva, and 38% were core participants. Those referred by a clinical site were almost twice as likely to be core participants. Those who directly visited the SPARK website or performed a Google search were more likely to be core participants than those who joined through social media. Discussion: Being a core participant may be associated with the “personal” connection and support provided by a clinical site and/or site staff, as well as greater motivation to seek research opportunities. Findings from this study underscore the value of adopting a multimodal recruitment approach that combines social media and a physical presence.

Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance. However, the Wasserstein distance does not follow a known distribution, posing challenges for the application of existing parametric statistical models. To tackle this issue, we introduce a unified topological inference framework centered on the Wasserstein distance. Our approach has no explicit model and distributional assumptions. The inference is performed in a completely data driven fashion. We apply this method to resting-state functional magnetic resonance images (rs-fMRI) of temporal lobe epilepsy patients collected from two different sites: the University of Wisconsin-Madison and the Medical College of Wisconsin. Importantly, our topological method is robust to variations due to sex and image acquisition, obviating the need to account for these variables as nuisance covariates. We successfully localize the brain regions that contribute the most to topological differences. A MATLAB package used for all analyses in this study is available at https://github.com/laplcebeltrami/PH-STAT.

Topological data analysis (TDA) provide tools that are becoming increasingly popular for analyzing multivariate time series data. One key aspect in analyzing multivariate time series is dependence between components. One application is on brain signal analysis. In particular, various dependence patterns in brain networks may be linked to specific tasks and cognitive processes. These dependence patterns may be altered by various neurological and cognitive impairments such as Alzheimer's and Parkinson's diseases, as well as attention deficit hyperactivity disorder (ADHD). Because there is no ground-truth with known dependence patterns in real brain signals, testing new TDA methods on multivariate time series is still a challenge. Our goal here is to develop novel statistical inference procedures via simulations. Simulations are useful for generating some null distributions of a test statistic (for hypothesis testing), forming confidence regions, and for evaluating the performance of proposed TDA methods. To the best of our knowledge, there are no methods that simulate multivariate time series data with potentially complex user-specified connectivity patterns. In this paper we present a novel approach to simulate multivariate time series with specific number of cycles/holes in its dependence network. Furthermore, we also provide a procedure for generating higher dimensional topological features.

Screening newborns using genome sequencing is being explored due to its potential to expand the list of conditions that can be screened. Previously, we proposed the need for large-scale pilot studies to assess the feasibility of screening highly penetrant genetic neurodevelopmental disorders. Here, we discuss the initial experience from the GUARDIAN study and the systemic gaps in clinical services that were identified in the early stages of the pilot study.

Abstract Liver fibrosis and cirrhosis have limited therapeutic options and represent a serious unmet patient need. Recent use of single‐cell RNA sequencing (scRNAseq) has identified enriched cell types infiltrating cirrhotic livers but without defining the microanatomical location of these lineages thoroughly. To assess whether fibrotic liver regions specifically harbor enriched cell types, we explored whether whole‐tissue spatial transcriptomics combined with scRNAseq and gene deconvolution analysis could be used to localize cell types in cirrhotic explants of patients with end‐stage liver disease (total n = 8; primary sclerosing cholangitis, n = 4; primary biliary cholangitis, n = 2, alcohol‐related liver disease, n = 2). Spatial transcriptomics clearly identified tissue areas of distinct gene expression that strongly correlated with the total area (Spearman r = 0.97, p = 0.0004) and precise location (parenchyma, 87.9% mean congruency; range, 73.1%–97.1%; fibrosis, 68.5% mean congruency; range, 41.0%–91.7%) of liver regions classified as parenchymal or fibrotic by conventional histology. Deconvolution and enumeration of parenchymal and fibrotic gene content as measured by spatial transcriptomics into distinct cell states revealed significantly higher frequencies of ACTA2+ FABP4+ and COL3A1+ mesenchymal cells, IL17RA+ S100A8+ and FCER1G+ tissue monocytes, VCAM1+ SDC3+ Kupffer cells, CCL4+ CCL5+ KLRB1+ and GZMA+ IL17RA+ T cells and HLA‐DR+, CD37+ CXCR4+ and IGHM+ IGHG+ B cells in fibrotic liver regions compared with parenchymal areas of cirrhotic explants. Conclusion: Our findings indicate that spatial transcriptomes of parenchymal and fibrotic liver regions express unique gene content within cirrhotic liver and demonstrate proof of concept that spatial transcriptomes combined with additional RNA sequencing methodologies can refine the localization of gene content and cell lineages in the search for antifibrotic targets.

The protein SLITRK2 plays an important role in synaptic communication. This study identifies X-linked SLITRK2 variants that underlie neurodevelopmental disorders by impairing excitatory synapses.

Circulatory system diseases and nervous system disorders often co-occur in patients. Here the authors use eMERGE and UK BioBank data to identify genomic regions associated with both phenotypes, providing insight into the relationship between these conditions.