Deciphering the molecular landscape of microcephaly in 87 Indian families by exome sequencing

Microcephaly is a frequent feature of neurodevelopmental disorders (NDDs). Our study presents the heterogeneous spectrum of genetic disorders in patients with microcephaly either in isolated form or in association with other neurological and extra-neural abnormalities. We present data of 91 patients from 87 unrelated families referred to our clinic during 2016–2020 and provide a comprehensive clinical and genetic landscape in the studied cohort. Molecular diagnosis using exome sequencing was made in 45 families giving a yield of 51.7%. In 9 additional families probable causative variants were detected. We identified disease causing variations in 49 genes that are involved in different functional pathways Among these, 36 had an autosomal recessive pattern, 8 had an autosomal dominant pattern (all inherited de novo), and 5 had an X-linked pattern. In 41 probands where sequence variations in autosomal recessive genes were identified 31 were homozygotes (including 16 from non-consanguineous families). The study added 28 novel pathogenic/likely pathogenic variations. The study also calls attention to phenotypic variability and expansion in spectrum as well as uncovers genes where microcephaly is not reported previously or is a rare finding. We here report phenotypes associated with the genes for ultra-rare NDDs with microcephaly namely ATRIP, MINPP1, PNPLA8, AIMP2, ANKLE2, NCAPD2 and TRIT1.     

Residential greenness and risks of depression: Longitudinal associations with different greenness indicators and spatial scales in a Finnish population cohort

We carried out a longitudinal study on the associations between residential greenness and depression risk in urban areas in Finland. Residential greenness indicators were estimated within various buffer sizes around individuals' home locations (selected n = 14424) using time-series of normalized differential vegetation index (NDVI) and CORINE land cover data (CLC). We estimated individuals’ cumulative exposure to residential greenness over a 5-years and 14-years follow-up. We used doctor-diagnosed depression and Beck Depression Inventory for depression assessment. Our multi-logistic model showed an inverse association between residential greenness and depression, implying lowered depression risk for individuals with higher residential greenness. The association was particularly evident when using NDVI-based residential greenness (within a buffer of 100 m radius) and doctor-diagnosis depression data, adjusted with individual-level covariates. The odds ratio was 0.56 (95% CI 0.33 to 0.96) for the 5-years follow-up, and 0.54 (95% CI 0.30 to 0.98) for the 14-years follow-up. The associations between CLC-based total residential green space and depression varied across the different buffer sizes. In general, all the associations depended on the type of depression assessment, quality of greenness indicators, and the spatial scale of analysis. The associations also varied across the socio-demographic groups and neighborhood socioeconomic disadvantage level.     

Left ventricular noncompaction associated with a pathogenic mutation in the MYH7 gene: Known mutation,different phenotype

Left ventricular noncompaction (LVNC) is a genetically heterogeneous cardiomyopathy, with familial and sporadic forms, but genetic testing only identifies a pathogenic mutation in a minority of cases. The main complications are heart failure, embolism and dysrhythmias. Herein we report a familial case of LVNC associated with a mutation in the MYH7 gene and review the literature regarding controversies in LVNC. A 50-year-old woman was referred to the cardiology clinic for palpitations. She underwent echocardiography and cardiac magnetic resonance imaging that revealed mild left ventricular systolic dysfunction and LVNC criteria. She had several episodes of non-sustained ventricular tachycardia and received an implantable cardioverter-defibrillator (ICD). Genetic testing revealed the c.1003G>C (p.Ala335Pro) mutation in the MYH7 gene. Familial screening showed clear genotype-phenotype cosegregation, which provided strong evidence for the pathogenic role of this mutation. To the best of our knowledge, this is the first report of LVNC associated with the p.Ala335Pro mutation in the MYH7 gene. This mutation has been described in hypertrophic cardiomyopathy, suggesting that the same pathogenic sarcomere mutation may be associated with different cardiomyopathies. This case also highlights the current difficulties regarding decisions on ICD implantation for primary prevention of sudden cardiac death in LVNC.     

Geographic Characteristics of Various Cancers in Yogyakarta Province,Indonesia: A Spatial Analysis at the Community Level

Background: Cancer remains a significant public health problem in Indonesia and worldwide. Yogyakarta Province has the largest number of cancer cases in Indonesia. Maps of the distribution of cancer cases are useful tools for stratification of cancer risk and for selective prevention strategies. The aim of this study was to determine the spatial distribution of cancer cases in Yogyakarta Province. Methods: Cancer patient data registered by the Yogyakarta Provincial Health Office during 2019-2020 were analysed in this study (n=9,933). To evaluate cancer pattern distributions, ArcGIS 10.2 and Excel 2016 software were used. Results: The mean participant age (± standard deviation) was 55.08 ± 15.46 years, and 79.40% were female. Breast and cervical cancer were the most frequently diagnosed, and the majority of patients were located in Sleman district. The incidence of all cancer types varied by county-level. The majority of cancer patients lived below the poverty line. Cancer screening rates were low, and screening was limited to breast and cervical cancer. Conclusion: Various types of cancers were identified in Yogyakarta, Indonesia; of them, breast and cervical cancer predominated. Most of the cancer patients were from Sleman district and economically poor areas. Geospatial techniques are useful for identifying environmental factors related to cancer and improving cancer control strategies and resource allocation.     

Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.     

Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

Applications of geospatial analyses in health research among homeless people: A systematic scoping review of available evidence

BackgroundUnequal housing access resulted in more than 150 million homeless people worldwide, with millions more expected to be added every year due to the ongoing climate-related crises. Homeless population has a counterproductive effect on the social, psychological integration efforts by the community and exposure to other severe health-related issues. Geographic Information Systems (GIS) have long been applied in urban planning and policy, housing and homelessness, and health-related research.MethodsWe used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to systematically review 24 articles collected from multiple databases (n = 10) that focused on health-related issues among homeless people and used geospatial analysis techniques in their research.ResultsOur findings indicated a geographic clustering of case study locations– 26 out of the 31 case study sites are from the USA and Canada. Studies used spatial analysis techniques to identify hotspots, clusters and patterns of patient location and population distribution. Studies also reported relationships among the location of homeless shelters and substance use, discarded needles, different infectious and non-infectious disease clusters.ConclusionMost studies were restricted in analyzing and visualizing the patterns and disease clusters; however, geospatial analyses techniques are useful and offer diverse techniques for a more sophisticated understanding of the spatial characteristics of the health issues among homeless people. Better integration of GIS in health research among the homeless would help formulate sensible policies to counter health inequities among this vulnerable population group.     

Association of regional socioeconomic deprivation and rurality with global developmental delay in early childhood: Data from mandatory school entry examinations in Germany

BackgroundFrom birth to young adulthood, health and development of young people are strongly linked to their living situation, including their family’s socioeconomic position (SEP) and living environment. The impact of regional characteristics on development in early childhood beyond family SEP has been rarely investigated. This study aimed to identify regional predictors of global developmental delay at school entry taking family SEP into consideration.MethodWe used representative, population-based data from mandatory school entry examinations of the German federal state of Brandenburg in 2018/2019 with n=22,801 preschool children. By applying binary multilevel models, we hierarchically analyzed the effect of regional deprivation defined by the German Index of Socioeconomic Deprivation (GISD) and rurality operationalized as inverted population density of the children’s school district on global developmental delay (GDD) while adjusting for family SEP (low, medium and high).ResultsFamily SEP was significantly and strongly linked to GDD. Children with the highest family SEP showed a lower odds for GDD compared to a medium SEP (female: OR=4.26, male: OR=3.46) and low SEP (female: OR=16.58, male: OR=12.79). Furthermore, we discovered a smaller, but additional and independent effect of regional socioeconomic deprivation on GDD, with a higher odds for children from a more deprived school district (female: OR=1.35, male: OR=1.20). However, rurality did not show a significant link to GDD in preschool children beyond family SEP and regional deprivation.ConclusionFamily SEP and regional deprivation are risk factors for child development and of particular interest to promote health of children in early childhood and over the life course.     

On estimands arising from misspecified semiparametric rate-based analysis of recurrent episodic conditions

Marginal rate-based analyses are widely used for the analysis of recurrent events in clinical trials. In many areas of application, the events are not instantaneous but rather signal the onset of a symptomatic episode representing a recurrent infection, respiratory exacerbation, or bout of acute depression. In rate-based analyses, it is unclear how to best handle the time during which individuals are experiencing symptoms and hence are not at risk. We derive the limiting value of the Nelson-Aalen estimator and estimators of the regression coefficients under a semiparametric rate-based model in terms of an underlying two-state process. We investigate the impact of the distribution of the episode durations, heterogeneity, and dependence on the asymptotic and finite sample properties of standard estimators. We also consider the impact of these features on power in trials designed to test intervention effects on rate functions. An application to a trial of individuals with herpes simplex virus is given for illustration.