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Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

PurposeTo investigate if accounting for a cup-to-disc ratio (CDR) genetic risk score (GRS) modified the association between large CDR and cognitive function among women.DesignThis was a retrospective study using data from the Women's Health Initiative.MethodsPatients with glaucoma or ocular hypertension were excluded. Large CDR was defined as ≥ 0.6 in either eye. Cognitive function was measured by the Modified Mini-Mental State Examination (3MSE). We used the combined effects from 13 single nucleotide polymorphisms (SNPs) to formulate the GRS for CDR. We used logistic regression to investigate associations between weighted GRS and large CDR, then a linear regression to assess the association between weighted GRS and 3MSE scores, and between weighted GRS, CDR, and 3MSE scores, adjusted for demographic and clinical characteristics.ResultsFinal analyses included 1,196 White women with mean age of 69.60 ± 3.62 years and 7.27% with large CDR. Mean GRS in women with and without large CDR was 1.51 ± 0.31 vs. 1.41 ± 0.36, respectively (p = 0.004). The odds of large CDR for a one unit increase in GRS was 2.30 (95% CI: (1.22, 4.36), p = 0.011). Adding the CDR GRS in the model with CDR and 3MSE, women with large CDR still had statistically significantly lower 3MSE scores than those without large CDR, yielding a predicted mean difference in 3MSE scores of 0.84 (p = 0.007).ConclusionsIndependent of the CDR GRS, women with large CDR had a lower cognitive function.

Wiedemann-Steiner syndrome (WSS) is an autosomal dominant disorder caused by monoallelic variants in KMT2A and characterized by intellectual disability and hypertrichosis. We performed a retrospective, multicenter, observational study of 104 individuals with WSS from five continents to characterize the clinical and molecular spectrum of WSS in diverse populations, to identify physical features that may be more prevalent in White versus Black Indigenous People of Color individuals, to delineate genotype-phenotype correlations, to define developmental milestones, to describe the syndrome through adulthood, and to examine clinicians' differential diagnoses. Sixty-nine of the 82 variants (84%) observed in the study were not previously reported in the literature. Common clinical features identified in the cohort included: developmental delay or intellectual disability (97%), constipation (63.8%), failure to thrive (67.7%), feeding difficulties (66.3%), hypertrichosis cubiti (57%), short stature (57.8%), and vertebral anomalies (46.9%). The median ages at walking and first words were 20 months and 18 months, respectively. Hypotonia was associated with loss of function (LoF) variants, and seizures were associated with non-LoF variants. This study identifies genotype-phenotype correlations as well as race-facial feature associations in an ethnically diverse cohort, and accurately defines developmental trajectories, medical comorbidities, and long-term outcomes in individuals with WSS.

Phacomatosis pigmentovascularis (PPV) comprises a family of rare conditions that feature vascular abnormalities and melanocytic lesions that can be solely cutaneous or multisystem in nature. Recently published work has demonstrated that both vascular and melanocytic abnormalities in PPV of the cesioflammea and cesiomarmorata subtypes can result from identical somatic mosaic activating mutations in the genes GNAQ and GNA11. Here, we present three new cases of PPV with features of the cesioflammea and/or cesiomarmorata subtypes and mosaic mutations in GNAQ or GNA11. To better understand the risk of potentially occult complications faced by such patients we additionally reviewed 176 cases published in the literature. We report the frequency of clinical findings, their patterns of co-occurrence as well as published recommendations for surveillance after diagnosis. Features assessed include: capillary malformation; dermal and ocular melanocytosis; glaucoma; limb asymmetry; venous malformations; and central nervous system (CNS) anomalies, such as ventriculomegaly and calcifications. We found that ocular findings are common in patients with phacomatosis cesioflammea and cesiomarmorata. Facial vascular involvement correlates with a higher risk of seizures (p = .0066). Our genetic results confirm the role of mosaic somatic mutations in GNAQ and GNA11 in phacomatosis cesioflammea and cesiomarmorata. Their clinical and molecular findings place these conditions on a clinical spectrum encompassing other GNAQ and GNA11 related disorders and inform recommendations for their management.

ObjectiveThis report describes the linkage between the National Health Interview Survey (NHIS) and air monitoring data from the U.S. Environmental Protection Agency (EPA). There have been few linkages of these data sources, partly because of restrictions on releasing geographic detail from NHIS on public-use files in order to protect participant confidentiality.MethodsPollution exposures for NHIS respondents were calculated by averaging the annual average exposure estimates from EPA air monitors both within 5, 10, 15, and 20 miles of the respondent's block-group location (which is available on restricted NHIS data files) and by county of residence. The 1987-2005 linked data files--referred to as NHIS-EPAAnnualAir--were used to describe the percentage of NHIS respondents linked and the median exposures by linkage method, survey year, and pollutant. Using the 2005 NHIS-EPAAnnualAir data file, the percentage linked and median exposure were described by respondent characteristics, linkage method, and pollutant.ResultsMany decisions were made to define pollution exposures for NHIS respondents, including monitor selection, location assignment for NHIS respondents, and geographic linkage criteria. Geographic linkage criteria for assigning area-level exposure estimates affected the percentage and composition of respondents included in the resulting linked sample. Median exposure estimates, however, were similar among geographic linkage methods.ConclusionNHIS-EPAAnnualAir data files for 1985 through 2005 are currently available to users in the NCHS Research Data Center.

ObjectiveThis report describes the linkage between the National Health Interview Survey (NHIS) and air monitoring data from the U.S. Environmental Protection Agency (EPA). There have been few linkages of these data sources, partly because of restrictions on releasing geographic detail from NHIS on public-use files in order to protect participant confidentiality.MethodsPollution exposures for NHIS respondents were calculated by averaging the annual average exposure estimates from EPA air monitors both within 5, 10, 15, and 20 miles of the respondent's block-group location (which is available on restricted NHIS data files) and by county of residence. The 1987-2005 linked data files--referred to as NHIS-EPAAnnualAir--were used to describe the percentage of NHIS respondents linked and the median exposures by linkage method, survey year, and pollutant. Using the 2005 NHIS-EPAAnnualAir data file, the percentage linked and median exposure were described by respondent characteristics, linkage method, and pollutant.ResultsMany decisions were made to define pollution exposures for NHIS respondents, including monitor selection, location assignment for NHIS respondents, and geographic linkage criteria. Geographic linkage criteria for assigning area-level exposure estimates affected the percentage and composition of respondents included in the resulting linked sample. Median exposure estimates, however, were similar among geographic linkage methods.ConclusionNHIS-EPAAnnualAir data files for 1985 through 2005 are currently available to users in the NCHS Research Data Center.