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One of the biggest complication in diabetes patients is chronic kidney disease (CKD), making it a tremendous burden on the country's public healthcare system. We have developed HealthVector Diabetes (HVD), a digital twin model that leverages generalized metabolic fluxes (GMF) to proficiently predict the onset of CKD and facilitate its early detection. Our HVD GMF model utilized commonly available clinical and physiological biomarkers as inputs for identification and prediction of CKD. We employed four diverse multiethnic cohorts: one Singaporean cohort (EVAS, n=289) and one North American cohort (NHANES, n=1044) for baseline CKD identification, and two multi-center Singaporean cohorts (CDMD, n=2119 and SDR, n=3627) for 3-year CKD prediction. We developed one identification model and two prediction models (with complete or incomplete parameters). The identification model demonstrated strong performance with an AUC ranging from 0.80 to 0.82. For prediction, with incomplete parameters, we achieved an AUC of 0.75, while the complete parameter model achieved an improved AUC of 0.86. Our model also effectively stratifies patients into low, moderate, and high-risk categories, with the high-risk category having the highest proportion (53.3-62.9%) of patients with CKD. Our method also reveals metabolic health profile differences among patient subgroups at baseline, indicating that patient subgroups who develop future CKD exhibit more deteriorated profiles. GMF-based clustering reveals distinct metabolic profile differences that act as drivers for CKD progression, and cluster distances map patient health trajectories. Our HVD GMF digital twin model has the ability to identify patients with baseline CKD and predict future CKD within a 3-year time frame. Furthermore, our approach enables risk stratification, subgrouping and clustering based on metabolic health profiles, positioning our model as a valuable clinical application tool for healthcare practitioners.

Dengue fever is a major public health concern in tropical regions, caused by four distinct serotypes. Sequential infection with a different serotype increases the risks of severe disease through antibody-dependent enhancement (ADE). Huge modeling efforts have focused on primary and heterologous secondary infections, while the dynamics of homologous secondary infections were overlooked due to the assumption of lifelong immunity preventing reinfections by the same serotype. Recent findings challenge the current understanding of dengue immunity. To explore immunological responses in various dengue infection scenarios, we use a within-host modeling framework that considers individual immunological varia- tions. These models are validated using empirical data. In addition to successfully capturing primary and heterologous secondary infection dynamics facilitated by ADE, this framework provides, for the first time, insights into homotypic reinfection dynamics and discusses its relevance in dengue transmission at the population level, with potential implications for disease prevention and control strategies.

Multimorbidity is an emerging challenge for healthcare systems globally. It is commonly defined as the co-occurrence of two or more chronic conditions in one person, but the suitability and utility of this concept beyond high-income settings is uncertain. This article presents the findings from an interdisciplinary research initiative that drew together 60 academic and applied partners working in 10 African countries to critically consider existing concepts and definitions of multimorbidity, to evaluate their utility and limitations, and to co-develop an context-sensitive, interdisciplinary conceptual framing. This iterative process was guided by the principles of grounded theory and involved focus- and whole-group discussions during a three-day concept-building workshop, thematic coding of workshop discussions, and further post-workshop iterative development and refinement. The three main thematic domains that emerged from workshop discussions were: the disease-centricity of current concepts and definitions; the need to foreground what matters to people living with multimorbidity (PLWMM), families, and other stakeholders; and the need for conceptual breadth and flexibility to accommodate the contributions of multiple disciplinary perspectives and heterogeneity within and between different African countries. These themes fed into the development of an expanded conceptual model that centres the catastrophic impacts multimorbidity often has for PLWMM, their families and support structures, for service providers, and for resource-constrained healthcare systems.

Background: Few studies have focused on factors associated with futile recanalization in acute anterior circulation stroke patients with large infarct cores who were treated with modern endovascular therapy (EVT). The aim of this study was to explore the factors associated with futile recanalization in patients with large ischemic strokes. Methods: This is a post hoc analysis of the ANGEL-ASPECT trial. Demographic and clinical characteristics, acute stroke workflow interval times, and imaging characteristics were compared between the futile and meaningful recanalization groups. A favorable outcome was defined as a 90-day mRS score 0-3, successful reperfusion was defined as eTICI 2b, 2c and 3 on final angiogram, and futile recanalization was defined as failure to achieve a favorable outcome despite successful reperfusion. Multivariate analysis was performed to identify the predictors of futile recanalization. Results: One hundred eighty-three patients were included in the final analysis; 91 (49.7%) patients had futile recanalization, and 92 (51.3%) patients had meaningful recanalization. In multivariable logistic regression analysis, older age (age [≥]68, OR=3.29, P=0.004), higher NIHSS score (NIHSS [≥]16, OR=3.33, P=0.003), diabetes (OR=3.23, P=0.017), larger final volume (FIV [≥]174.7, OR=6.79, P<0.001), postoperative respiratory failure (OR=14.56, P=0.01), and female sex (OR=2.78, P=0.01) were independent predictors of futile recanalization. Conclusions: Futile recanalization occurred in approximately half of acute stroke patients with a large infarct core following endovascular treatment. Old age, high baseline NIHSS score, diabetes mellitus, large FIV and respiratory failure were independent predictors of futile recanalization after endovascular therapy for large ischemic strokes. Stroke-related pneumonia control may improve prognosis.

Doxycycline as post-exposure prophylaxis (doxy-PEP) reduces the risk of gonorrhea, chlamydia, and syphilis in studies of men who have sex with men (MSM) and transgender women (TGW) on HIV Pre-exposure Prophylaxis (PrEP) and people living with HIV (PLWH)). Doxy-PEP is an important tool to address the increasing burden of sexually transmitted infections (STIs), but there is concern that increased consumption of doxycycline may drive antimicrobial resistance. We estimated the expected increase in antibiotic use in the US under several doxy-PEP prescribing scenarios. We accounted for doses of antibiotics that may be averted due to the prevention of chlamydia, gonorrhea, and syphilis infections by doxy-PEP. Under a scenario of 75% adoption among the eligible population, with rates of consumption similar to the DoxyPEP trial population, monthly antibiotic consumption would increase by around 2.52 million doses, driven by doxy-PEP consumption of 2.58 million doses and less 62.1 thousand antibiotic doses that would otherwise have been used for chlamydia, gonorrhea, and syphilis treatment.

Background: Children who develop a psychiatric disorder often also develop additional comorbid psychiatric conditions, ultimately impacting prognosis, outcomes, and treatment planning. In this cross-sectional study using the ABCD dataset, the authors set out to identify distinct comorbidity profiles using comorbidity network analysis and any associated clinical correlates of behavior and structural neuroimaging markers. Methods: Structural magnetic resonance imaging and psychometric testing were obtained from 7077 eligible children between the ages of 9-10 in the ABCD dataset. Children were separated into the typically developing group and the psychiatric group based on the presence of a DSM-V diagnosis. Results: Three comorbidity profiles across gender emerged using comorbidity network analysis. Girls with the ADHD - ODD (AO) comorbidity profile and sparse comorbidity profile had thicker left superior frontal gyri compared to typically developing children. Boys and girls with the ADHD - ODD comorbidity profile had significantly higher externalizing scores compared to typically developing children. The ADHD-OCD-Specific Phobia (AOS) profile among boys had significantly higher internalizing scores, while the AO profile had significantly higher internalizing scores for girls. The AOS profile for boys and the AO profile for girls had significantly higher total problem scores compared to typically developing children. Conclusion: Comorbidity network analysis successfully identified comorbidity profiles associated with unique neurobiological markers and behavioral correlates and is a feasible technique for the investigation of comorbid psychiatric conditions.

Introduction Cancer outcome is largely determined by stage at diagnosis. We hypothesised that people living in Low- and Middle-Income Countries may be reaching diagnosis at an early stage, reflecting growth in awareness of the disease and its symptoms. We examined stage at diagnosis for four common cancers presenting at a referral centre in Nigeria. Methods A retrospective review of case-records from cases treated for four common cancers (colorectal, uterine cervix, breast and prostate) at University College Hospital, Ibadan over two epochs: 2012-2013 and 2017-2018. Results There is no evidence that cases were diagnosed at an earlier stage in the later epoch. Seventy-five percent of cases were diagnosed at late stage (III or IV) in the second epoch, vs seventy percent in the first epoch. Conclusion There is no evidence in the data that the problem of late presentation of common cancers is reducing in Oyo State, Nigeria.

Background: Indoor and outdoor air pollution levels are associated with poor asthma outcomes in children. However, few studies have evaluated whether breathing zone pollutant levels associate with asthma outcomes. Objective: Determine breathing zone exposure levels of NO2, O3, total PM10 and PM10 constituents among children with exacerbation-prone asthma, and examine correspondence with in-home and community measurements and associations with outcomes. Methods: We assessed children's personal breathing zone exposures using wearable monitors. Personal exposures were compared to in-home and community measurements and tested for association with lung function, asthma control, and asthma exacerbations. Results: 81 children completed 219 monitoring sessions. Correlations between personal and community levels of PM10, NO2, and O3 were poor, whereas personal PM10 and NO2 levels correlated with in-home measurements. However, in-home monitoring underdetected brown carbon (Personal:79%, Home:36.8%) and ETS (Personal:83.7%, Home:4.1%) personal exposures, and detected black carbon in participants without these personal exposures (Personal: 26.5%, Home: 96%). Personal exposures were not associated with lung function or asthma control. Children experiencing an asthma exacerbation within 60 days of personal exposure monitoring had 1.98, 2.21 and 2.04 times higher brown carbon (p<0.001), ETS (p=0.007), and endotoxin (p=0.012), respectively. These outcomes were not associated with community or in-home exposure levels. Conclusions: Monitoring pollutant levels in the breathing zone is essential to understand how exposures influence asthma outcomes, as agreement between personal and in-home monitors is limited. Inhaled exposure to PM10 constituents modifies asthma exacerbation risk, suggesting efforts to limit these exposures among high-risk children may decrease their asthma burden.

Background: Despite the widespread endorsement of 24-hour movement guidelines (physical activity, sleep, screentime) for youth, no standardized processes for categorizing guideline achievement exists. Different data handling procedures prior to classification (averaging movement behavior across multiple days, categorizing the number days guidelines are met by each participant) may produce different estimates and several methods are used by researchers. The purpose of this study was to illustrate the impact of different data handling strategies on the proportion of children meeting 24-hour movement guidelines (24hrG) and subsequent associations with overweight and obesity. Methods: A subset of 524 children (ages 5-12yrs) from an observational cohort with complete 24-hour behavior measures on at least 10 days was used to compare the impact of data handling strategies on estimates of meeting 24hrG. Physical activity and sleep were measured via accelerometry. Screentime was measured via parent self-report. Comparison of meeting 24hrG were made using 1) average of behaviors across all days (AVG-24hr), 2) classifying each day as meeting/not meeting 24hrG and evaluating the percentage meeting 24hrG from 10-100% of their measured days (DAYS-24hr), and 3) the average of a random sample of 4 days across 10 iterations (RAND-24hr). The number of times participants met guidelines across all 10 random samples was calculated to examine estimate variability. A second subset of children (N=475) with height and weight data was used to explore the influence of each data handling strategy on children meeting guidelines and the odds of overweight and obesity via logistic regression. Results: Classification for AVG-24hr resulted in 14.7% of participants meeting 24hrG. Classification for DAYS-24hr resulted in 63.5% meeting 24hrG on 10% of measured days, 26.1% meeting 24hrG on 50-80% of measured days with <1% meeting 24hrG on 100% of days. Classification for RAND-24hr resulted in 15.9% of participants meeting 24hrG. Across 10 iterations, 63.6% of participants never met 24hrG regardless of the days sampled, 3.4% always met 24hrG, with the remaining 33.0% classified as meeting 24hrG for at least one of the 10 random iterations of days. Each data handling strategy produced different odds of overweight and obesity for children meeting the guidelines. Conclusions: Varying estimates of meeting the 24hrG and the odds of overweight and obesity results from different data handling strategies and days sampled. Each strategy has strengths and weaknesses. Understanding the impact of each approach on estimates is essential to identifying the association of meeting 24hrG with health outcomes and for identifying day-specific factors that may be associated with meeting 24hrG on a given day.

Background: Given the high global seroprevalence of SARS-CoV-2, understanding the risk of reinfection becomes increasingly important. Models developed to track trends in reinfection risk should be robust against possible biases arising from imperfect data observation processes. Objectives: We performed simulation-based validation of an existing catalytic model designed to detect changes in the risk of reinfection by SARS-CoV-2. Methods: The catalytic model assumes the risk of reinfection is proportional to observed infections. Validation involved using simulated primary infections, consistent with the number of observed infections in South Africa. We then simulated reinfection datasets that incorporated different processes that may bias inference, including imperfect observation and mortality, to assess the performance of the catalytic model. A Bayesian approach was used to fit the model to simulated data, assuming a negative binomial distribution around the expected number of reinfections, and model projections were compared to the simulated data generated using different magnitudes of change in reinfection risk. We assessed the approach's ability to accurately detect changes in reinfection risk when included in the simulations, as well as the occurrence of false positives when reinfection risk remained constant. Key Findings: The model parameters converged in most scenarios leading to model outputs aligning with anticipated outcomes. The model successfully detected changes in the risk of reinfection when such a change was introduced to the data. Low observation probabilities (10%) of both primary- and re-infections resulted in low numbers of observed cases from the simulated data and poor convergence. Limitations: The model's performance was assessed on simulated data representative of the South African SARS-CoV-2 epidemic, reflecting its timing of waves and outbreak magnitude. Model performance under similar scenarios may be different in settings with smaller epidemics (and therefore smaller numbers of reinfections). Conclusions: Ensuring model parameter convergence is essential to avoid false-positive detection of shifts in reinfection risk. While the model is robust in most scenarios of imperfect observation and mortality, further simulation-based validation for regions experiencing smaller outbreaks is recommended. Caution must be exercised in directly extrapolating results across different epidemiological contexts without additional validation efforts.

TwinsMX registry is a national research initiative in Mexico that aims to understand the complex interplay between genetics and environment in shaping physical and mental health traits among the country's population. With a multidisciplinary approach, TwinsMX aims to advance our knowledge of the genetic and environmental mechanisms underlying ethnic variations in complex traits and diseases, including behavioral, psychometric, anthropometric, metabolic, cardiovascular, and mental disorders. With information gathered from over 2800 twins, this article updates the prevalence of several complex traits; and describes the advances and novel ideas we have implemented such as magnetic resonance imaging. The future expansion of the TwinsMX registry will enhance our comprehension of the intricate interplay between genetics and environment in shaping health and disease in the Mexican population. Overall, this report describes the progress in the building of a solid database which shall allow to study complex traits in the Mexican population, valuable not only for our consortium but for the worldwide scientific community by providing new insights of understudied genetically admixed populations.

Objective: Beginning in October 2021 in the US and elsewhere, cases of severe pediatric hepatitis of unknown etiology were identified in young children. While the adenovirus and adenovirus-associated virus have emerged as leading etiologic suspects, we attempted to investigate a potential role for SARS-CoV-2 in the development of subsequent liver abnormalities. Design: We conducted a study utilizing retrospective cohorts of de-identified, aggregated data from the electronic health records of over 100 million patients contributed by US health care organizations. Results: Compared to propensity-score-matched children with other respiratory infections, children aged 1-10 years with COVID-19 had a higher risk of elevated transaminases (Hazard ratio (HR) (95% Confidence interval (CI)) 2.16 (1.74-2.69)) or total bilirubin (HR (CI) 3.02 (1.91-4.78)), or new diagnoses of liver diseases (HR (CI) 1.67 (1.21-2.30)) from one to six months after infection. Patients with pre-existing liver abnormalities, liver abnormalities surrounding acute infection, younger age (1-4 years), or illness requiring hospitalization all had similarly elevated risk. Children who developed liver abnormalities following COVID-19 had more pre-existing conditions than those who developed abnormalities following other infections. Conclusion: These results indicate that SARS-CoV-2 may prime the patient for subsequent development of liver infections or non-infectious liver diseases. While rare (~1 in 1,000), SARS-CoV-2 is a risk for subsequent abnormalities in liver function or the diagnosis of diseases of the liver.

Background: We assessed the association between antibody concentration within 5 days of symptom onset and COVID-19 illness among patients enrolled in a test-negative study. Methods: From October 2021 to June 2022, study sites in seven states enrolled and tested respiratory specimens from patients of all ages presenting with acute respiratory illness for SARS-CoV-2 infection using rRT-PCR. In blood specimens, we measured concentration of anti-SARS-CoV-2 antibodies against the ancestral strain spike protein receptor binding domain (RBD) and nucleocapsid (N) antigens in standardized binding antibody units (BAU/mL). Percent reduction in odds of symptomatic COVID-19 by anti-RBD antibody was estimated using logistic regression modeled as (1-adjusted odds ratio of COVID-19)x100, adjusting for COVID-19 vaccination status, age, site, and high-risk exposure. Results: A total of 662 (33%) of 2,018 symptomatic patients tested positive for acute SARS-CoV-2 infection. During the Omicron-predominant period, geometric mean anti-RBD binding antibody concentrations measured 823 BAU/mL (95% CI:690 to 981) among COVID-19 case-patients versus 1,189 BAU/mL (95% CI:1,050 to 1,347) among SARS-CoV-2 test-negative patients. In the adjusted logistic regression, increasing levels of anti-RBD antibodies were associated with reduced odds of COVID-19 for both Delta and Omicron infections. Conclusion: Higher anti-RBD antibodies in patients were associated with protection against symptomatic COVID-19 during emergence of SARS-CoV-2 Delta and Omicron variants.

Background/Aims: The primary objective was to determine how structural and functional parameters influence the vision-related quality of life (VRQoL) in patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD). Methods: This prospective, non-interventional, natural-history "Directional Spread in Geographic-Atrophy" study was conducted at the University Eye Hospital in Bonn, enrolling 82 patients with bilateral GA. Parameters such as GA location (assessed by the Early Treatment Diabetic Retinopathy Study grid), best-corrected visual acuity (BCVA), low-luminance visual acuity (LLVA), reading acuity, and speed were examined. The association between these parameters and VRQoL, as gauged using the National Eye Institute Visual Function Questionnaire 25 (NEI VFQ-25), was analyzed through the least absolute shrinkage and selection operator with linear mixed-effects models. Results: The average total GA area observed was 2.9 +/- 1.2 mm2 (better eye) and 3.1 +/- 1.3 mm2 (worse eye). The VRQoL scores for distance and near activities were most associated with the inner lower and inner left subfields of the better eye. For foveal-sparing patients, the LLVA of the better eye was the predominant determinant impacting all VRQoL scales. Conclusion: GA location, specifically the inner lower and inner left subfields of the better eye, has a notable effect on VRQoL in GA patients. LLVA stands out as especially vital in foveal-sparing patients, underscoring the importance for clinicians to incorporate considerations of GA location and functional parameters into their risk-benefit assessments for emerging treatments.

Background Compared to cancer-free persons, cancer survivors of the same chronological age (CA) have increased physiological dysfunction, i.e., higher biological age (BA), which may lead to higher morbidity and mortality. We estimated BA using eight aging metrics: BA computed by Klemera Doubal method (KDM-BA), phenotypic age (PhenoAge), five epigenetic clocks (ECs, Horvath, Hannum, Levine, GrimAge, and pace of aging (POA)), and subjective age (SA). We tested if aging constructs were associated with total cancer prevalence and all-cause mortality in cancer survivors and controls, i.e., cancer-free persons, in the Health and Retirement Study (HRS), a large population-based study. Methods In 2016, data on BA-KDM, PhenoAge, and SA were available for 946 cancer survivors and 4,555 controls; data for the five ECs were available for 582 cancer survivors and 2,805 controls. Weighted logistic regression was used to estimate the association between each aging construct and cancer prevalence (odds ratio, OR, 95%CI). Weighted Cox proportional hazards regression was used to estimate the associations between each aging construct and cancer incidence as well as all-cause mortality (hazard ratio, HR, 95%CI). To study all BA metrics (except for POA) independent of CA, we estimated age acceleration as residuals of BA regressed on CA. Results Age acceleration for each aging construct and POA were higher in cancer survivors than controls. In a multivariable-adjusted model, five aging constructs (age acceleration for Hannum, Horvath, Levine, GrimAge, and SA) were associated with cancer prevalence. Among all cancer survivors, age acceleration for PhenoAge and four ECs (Hannum, Horvath, Levine, and GrimAge), was associated with higher all-cause mortality over 4 years of follow-up. PhenoAge, Hannum, and GrimAge were also associated with all-cause mortality in controls. The highest HR was observed for GrimAge acceleration in cancer survivors: 2.03 (95% CI, 1.58-2.60). In contrast, acceleration for KDM-BA and POA was significantly associated with mortality in controls but not in cancer survivors. When all eight aging constructs were included in the same model, two of them (Levine and GrimAge) were significantly associated with mortality among cancers survivors. None of the aging constructs were associated with cancer incidence. Conclusion Variations in the associations between aging constructs and mortality in cancer survivors and controls suggests that aging constructs may capture different aspects of aging and that cancer survivors may be experiencing age-related physiologic dysfunctions differently than controls. Future work should evaluate how these aging constructs predict mortality for specific cancer types.

Background: Despite patient interest in knowing whether diet is linked to multiple myeloma (MM), there is limited research on dietary patterns and MM risk. Two studies have assessed this risk, albeit with a small number of MM cases. The EPIC-Oxford cohort and Oxford Vegetarian study (65 MM cases) showed that fish eaters, vegetarians and vegans had significantly reduced MM risk compared to meat eaters. The Nurses Health Study and Health Professionals Follow-up Study (478 MM cases) showed a significantly increased MM risk in men with Empirical Dietary Inflammatory Pattern. Methods: The NIH-AARP Diet and Health study is a prospective cohort of 567,169 persons who completed a food frequency questionnaire in 1995-1996 and were followed until December 2011. Healthy Eating Index-2015 (HEI-2015), Healthy Diet Score (HDS), alternate Mediterranean Diet (aMED) and healthful Plant-based Diet Index (hPDI) scores were calculated using a priori defined methods and grouped into quartiles, with higher scores reflecting healthier eating patterns. We prospectively evaluated the association between pre-diagnosis dietary patterns and MM incidence in this cohort. Hazard ratios (HR) and 95% confidence intervals (95%CI) were estimated using multivariate Cox proportional hazards models adjusted for age at study entry, sex, race, body mass index, education, and total energy intake (by residual method). Sensitivity analysis was conducted to assess reverse causality by excluding MM cases diagnosed within one year of follow-up. Results: Among 392,589 participants (after exclusions), a total of 1,366 MM cases (59% males; 92% non-Hispanic whites) were identified during the follow-up period. Analysis revealed a significant association between hPDI scores and reduced MM risk (highest vs lowest quartile, HR 0.85; 95%CI 0.73-1.0; p=0.043) (Table). In sensitivity analysis (1,302 MM cases), the association was no longer significant (HR 0.87; 95%CI 0.74-1.03; p 0.09) but trended in the same direction. This may be due to small sample size, given MM is a rare disease. HEI-2015, HDS and aMED scores were not associated with MM risk. Conclusions: A healthful plant-based diet was associated with reduced MM risk in the NIH-AARP cohort. These results will help oncologists and patients make informed choices about their diet. To our knowledge, this is the largest epidemiologic study to date assessing pre-diagnosis dietary patterns and MM risk.

Background: Methylenetetrahydrofolate reductase (MTHFR) small nucleotide polymorphisms (SNPs) have been suggested as risk, prognostic, and predictive factors for colorectal cancer in various populations, but have not been validated so far. The aim of this study was to analyze the association of MTHFR C677T (rs1801133) and A1298C (rs1801131) small nucleotide polymorphisms with the risk of rectal cancer as well as the response to neoadjuvant chemoradiotherapy (nCRT) based on 5-Fluorouracil (5-FU)/leucovorin (LV) in the locally advanced setting. Patients and methods: A total of 102 patients with locally advanced rectal cancer (LARC) and 119 healthy controls were included in this case-control study. Restriction fragment length polymorphism analysis (PCR-RFLP) was used for MTHFR genotyping. Results: Using dominant and recessive models, it was found that the MTHFR 667C allele and the 1298A allele were significantly associated with rectal cancer as low-penetrant factors. Combined genotype analysis highlighted the protective role of the 677CT/1298AC genotype and increased risk for rectal cancer development for carriers of 677CC/1298AA. Haplotype analysis indicated that carriers of haplotype 677C/1298A have an increased risk for rectal cancer development while the haplotype 677T/1298A has a protective role. No significant association with response to chemoradiotherapy was found. Conclusion: Our data point to MTHFR 667C allele and 1298A alleles as low-penetrant risk factors for rectal cancer in our population. To the best of our knowledge, this is the first study of this type performed on the Slavic population in the Western Balkan area which might be useful for future meta-analyses and the construction of genetic cancer risk prediction panels, as various population-based factors might also be significant in this setting.

Open spina bifida (SB) remains one of the most common congenital anomalies and associates with significant comorbidities in the fetus, which may, in part, be driven by placental maldevelopment. We hypothesised that placental pathologies and maldevelopment would be more prevalent in fetuses with SB compared to fetuses without congenital anomalies. Placental histopathology (H&E-stained slides) and transcriptome (Clariom DTM microarray) were evaluated for fetuses with isolated open SB undergoing either pregnancy terminations or term deliveries (cases; n=12) and control fetuses without congenital anomalies having term or preterm births (n=22). Associations between study group and placental histopathology were adjusted for fetal sex and gestational age [GA] at delivery. Relationships between placental histopathology and select placental gene expression signatures were also evaluated. Case placentae had lower placental weight than controls (median [IQR]: 263g [175, 370] vs. 455 [378, 560], p=0.001). Placental villi structural phenotype was different in cases, who had a higher proportion of immature intermediate villi than controls (32.5% [6.3, 56.3] vs. 10% [5, 13.8], p=0.01), but similar proportions of mature intermediate (10% [5, 10] vs. 10% [8.75, 11.25]) and terminal villi (22.5% [11.3, 43.8] vs. 30 [20, 36.3]), and similar odds of having many syncytial knots (adjusted odds ratio [aOR]=6 [0.2, 369]) as full-term born controls. Cellular phenotypic differences in case placentae included higher odds of having many Hofbauer cells (aOR=16.2 [1.4, 580], p=0.02) and a thick syncytial membrane (aOR=146 [3, 3.46e5], p=0.007). Expression in gene pathways related to immune/inflammatory processes, spinal cord injury, and Hedgehog and Wnt signaling were associated with placental maturity in cases. This study is the first to characterize placental histopathology in a contemporary cohort of fetuses with SB. Improved knowledge on placental histopathological and genetic phenotypes in spina bifida increases our understanding of mechanisms that may drive comorbidities to ultimately reduce offspring morbidity and mortality.

Background: Autonomic dysfunction is one of the most common non-motor symptoms in Parkinson's disease (PD). Whether autonomic dysfunction contributes to disease progression and brain network abnormalities in PD remain largely unknown. The objective of this study is to evaluate how autonomic dysfunction affects clinical features and brain networks of PD patients. Methods: PD patients from Parkinson's Progression Markers Initiative (PPMI) database were included if they received magnetic resonance imaging. According to the scores of Scale for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), PD patients were classified into lower quartile group (SCOPA-AUT score rank: 0%~25%), interquartile group (SCOPA-AUT score rank: 26%~75%), and upper quartile group (SCOPA-AUT score rank: 76%~100%) based on their SCOPA-AUT score quartiles to examine how autonomic dysfunction shapes clinical manifestations and brain networks. Results: PD patients in the upper quartile group showed more severe motor and non-motor symptoms, as well as more deficits in dopamine transporter binding compared to lower quartile group. Additionally, they also showed statistically different topological properties in structural and functional network compared to lower quartile group. Both structural and functional network metrics mediated the effects of autonomic dysfunction on clinical symptoms of PD patients. Reduced dopamine transporter binding also contributed to the effects of autonomic dysfunction on disease burden of PD patients. Conclusions: PD patients with more severe autonomic dysfunction exhibit worse disease and impairment of brain network topology. Both network topology and striatal dopamine depletion mediate the effects of autonomic dysfunction on clinical symptoms of PD patients.

Background and objectives: Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL. Methods: A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2. Results: 59 adults with MS had at least 1 7T follow-up visit (mean follow-up time 2 {+/-} 0.5 years). 9 had 'active' relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had 'stable' RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010ul, range 13-9888 vs median 267ul, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183ul, range 270-9888 vs median 321ul, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS. Discussion: CL formation is rare in people with stable WML, even in those with worsening disa-bility. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.