Inter-individual Heterogeneity Research Articles

Predecisional information search adaptively reduces three types of uncertainty

How do people search for information when they are given the opportunity to freely explore their options? Previous research has suggested that people focus on reducing uncertainty before making a decision, but it remains unclear how exactly they do so and whether they do so consistently. We present an analysis of over 1,000,000 information-search decisions made by over 2,500 individuals in a decisions-from-experience setting that cleanly separates information search from choice. Using a data-driven approach supported by a formal measurement framework, we examine how people allocate samples to options and how they decide to terminate search. Three major insights emerge. First, predecisional information search has at least three drivers that can be interpreted as reducing three types of uncertainty: structural, estimation, and computational. Second, the selection of these drivers of information search is adaptive, sequential, and guided by environmental knowledge that integrates prior expectations, task instructions, and personal experiences. Third, predecisional information search exhibits substantial interindividual heterogeneity, with individuals recruiting different drivers of information search. Together, these insights suggest that human information search is complex in ways that cannot be fully explained by monolithic accounts of information search, including proposals focused on estimation uncertainty or cost-benefit analysis. We conclude that broader theories of human information-search behavior are necessary.

Modelling post-chemotherapy stem cell dynamics in the bone marrow niche of AML patients

Acute myeloid leukemia (AML) is a stem cell-driven malignancy of the blood forming (hematopoietic) system. Despite of high dose chemotherapy with toxic side effects, many patients eventually relapse. The “7+3 regimen”, which consists of 7 days of cytarabine in combination with daunorubicin during the first 3 days, is a widely used therapy protocol. Since peripheral blood cells are easily accessible to longitudinal sampling, significant research efforts have been undertaken to characterize and reduce adverse effects on circulating blood cells. However, much less is known about the impact of the 7+3 regimen on human hematopoietic stem cells and their physiological micro-environments, the so-called stem cell niches. One reason for this is the technical inability to observe human stem cells in vivo and the discomfort related to bone marrow biopsies. To better understand the treatment effects on human stem cells, we consider a mechanistic mathematical model of the stem cell niche before, during and after chemotherapy. The model accounts for different maturation stages of leukemic and hematopoietic cells and considers key processes such as cell proliferation, self-renewal, differentiation and therapy-induced cell death. In the model, hematopoietic (HSCs) and leukemic stem cells (LSCs) compete for a joint niche and respond to both systemic and niche-derived signals. We relate the model to clinical trial data from literature which longitudinally quantifies the counts of hematopoietic stem like (CD34+CD38-ALDH+) cells at diagnosis and after therapy. The proposed model can capture the clinically observed interindividual heterogeneity and reproduce the non-monotonous dynamics of the hematopoietic stem like cells observed in relapsing patients. Our model allows to simulate different scenarios proposed in literature such as therapy-related impairment of the stem cell niche or niche-mediated resistance. Model simulations suggest that during the post-therapy phase a more than 10-fold increase of hematopoietic stem-like cell proliferation rates is required to recapitulate the measured cell dynamics in patients achieving complete remission. We fit the model to data of 7 individual patients and simulate variations of the treatment protocol. These simulations are in line with the clinical finding that G-CSF priming can improve the treatment outcome. Furthermore, our model suggests that a decline of HSC counts during remission might serve as an indication for salvage therapy in patients lacking MRD (minimal residual disease) markers.

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the ‘last in, first out’ mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

The First Comprehensive Description of the Platelet Single Cell Transcriptome.

Platelet single cell sequencing can be implemented with appropriate technical refinements to ensure optimal isolation without exogenous activation. In comparison to bulk sequencing techniques, single cell analysis affords the ability to exclude contaminating cells enabling examination of the authentic platelet transcriptome. This is critically important as contaminating cells contain far more RNA ultimately skewing results of transcriptomic analysis.Most platelets do not contain significant levels of commonly expected transcripts such as ITGA2B, GP1B, TREML1. In the context of recent data, our single cell transcriptomic data supports the intradividual and interindividual heterogeneity of the platelet transcriptome. The lung megakaryocyte signature is not disguisable in peripheral platelets. Further studies are needed to understand sources of RNA within platelets and the impact of the platelet microenvironment.

Population clustering of structural brain aging and its association with brain development.

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the 'last in, first out' mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Design of the VOILA-intervention study: A 12-week nutrition and resistance exercise intervention in metabolic or mobility compromised Dutch older adults and the response on immune-metabolic, gut and muscle health parameters

BackgroundExercise and nutrition interventions can slow ageing-induced decline in physiology. However, effects are heterogeneous and usually studied separately per outcome domain. In the VOILA study, we simultaneously study various health outcomes relevant for older adults and the inter-individual heterogeneity in response to a lifestyle intervention. MethodsVOILA is a 12-week lifestyle intervention in 3 groups of older adults (≥60 years), with compromised mobility (n=50), compromised metabolic health (n=50), or recovering from total knee replacement (TKR, n=70, of which 20 randomized to standard care only). The intervention includes high-intensity resistance exercise training thrice weekly, nutritional counselling, and nutritional supplements every morning and evening (including 20-25g whey protein and (evening only) 5.5g Biotis™ GOS). We measure immune-metabolic, gut health, muscle mass and physical functioning at baseline and after completion of the intervention/standard care. An additional reference group of healthy older adults (n=50) will undergo baseline measurements only. DiscussionImprovements in various physiological systems are expected, but with differences between groups/individuals. This study will provide insights into how the physiological state of older adults influences the extent of lifestyle-induced health improvements to create better tailored interventions to attenuate biological ageing and improve the health span of subgroups and individuals.

Analysis of Morphologic Classification System for Acute Promyelocytic Leukemia and Its Correlation with Laboratory Tests and FLT3-ITD Mutation

To establish a morphologic classification system for characterizing blast cells in patients with acute promyelocytic leukemia (APL) and analyze the correlation of different APL morphologic characteristics with conventional tests and genetic variants. Based on the morphological characteristics of APL blast cells, a classification system of 14 categories was established to characterize the inter- and intra-individual cellular morphological heterogeneity of patients. The classification system was used for the morphological analysis of 40 APL patients, and the classification results were statistically analyzed with the patients' conventional test indexes and gene variant characteristics to analyze the correlation of different APL blast cell morphological features with conventional test indexes and gene variants. In the FLT3-ITD mutation-positive group, there were significantly fewer cells with regular nuclear shape, hyper granularity, and missing Auer rods (category 1) than in the FLT3 mutation-negative group (P < 0.05). The activated partial thromboplastin (APTT) was significantly longer in the group with regular nucleus compared to the group with irregular nucleus (P < 0.05). In the hypo-granular group, the APTT was also significantly longer compared to the hyper-granular group (P < 0.01), and the proportion of myeloid blast cells was relatively lower (P < 0.05). The peripheral blood white blood cell counts, D-dimer, lactate dehydrogenase and proportion of bone marrow blast cells were significantly higher in the Auer rods (-) group than Auer rods increasing group (all P < 0.05). The newly established morphologic classification system in this study can objectively characterize different types of APL blast cells, which helps to better assess the intra- and inter-individual heterogeneity of APL blast cells, and further use in accurately analyzing the correlation of morphological phenotypes with biological properties of APL.

Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping.

Unsupervised learning, particularly clustering, plays a pivotal role in disease subtyping and patient stratification, especially with the abundance of large-scale multi-omics data. Deep learning models, such as variational autoencoders (VAEs), can enhance clustering algorithms by leveraging inter-individual heterogeneity. However, the impact of confounders-external factors unrelated to the condition, e.g. batch effect or age-on clustering is often overlooked, introducing bias and spurious biological conclusions. In this work, we introduce four novel VAE-based deconfounding frameworks tailored for clustering multi-omics data. These frameworks effectively mitigate confounding effects while preserving genuine biological patterns. The deconfounding strategies employed include (i) removal of latent features correlated with confounders, (ii) a conditional VAE, (iii) adversarial training, and (iv) adding a regularization term to the loss function. Using real-life multi-omics data from The Cancer Genome Atlas, we simulated various confounding effects (linear, nonlinear, categorical, mixed) and assessed model performance across 50 repetitions based on reconstruction error, clustering stability, and deconfounding efficacy. Our results demonstrate that our novel models, particularly the conditional multi-omics VAE (cXVAE), successfully handle simulated confounding effects and recover biologically driven clustering structures. cXVAE accurately identifies patient labels and unveils meaningful pathological associations among cancer types, validating deconfounded representations. Furthermore, our study suggests that some of the proposed strategies, such as adversarial training, prove insufficient in confounder removal. In summary, our study contributes by proposing innovative frameworks for simultaneous multi-omics data integration, dimensionality reduction, and deconfounding in clustering. Benchmarking on open-access data offers guidance to end-users, facilitating meaningful patient stratification for optimized precision medicine.

Host heterogeneity in humoral bactericidal activity can be complement independent.

Humoral bactericidal activity was first recognized nearly a century ago. However, the extent of inter-individual heterogeneity and the mechanisms underlying such heterogeneity beyond antibody or complement systems have not been well studied. The plasma bactericidal activity of five healthy volunteers were tested against 30 strains of Gram-negative uropathogens, Klebsiella pneumoniae and Escherichia coli, associated with bloodstream infections. IgG and IgM titers specific to K. pneumoniae strains KP13883 and KPB1 were measured by ELISA, and complement inhibitor was used to measure the contribution of complement-induced killing. Furthermore, MALDI-TOF mass spectrometry was conducted to determine the metabolomic components of plasma with bactericidal properties in 25 healthy individuals using Bayesian inference of Pearson correlation between peak intensity and colony counts of surviving bacteria. Plasma bactericidal activity varied widely between individuals against various bacterial strains. While individual plasma with higher IgM titers specific to K. pneumoniae strain KP13883 showed more efficient killing of the strain, both IgM and IgG titers for K. pneumoniae strain KPB1 did not correlate well with the killing activity. Complement inhibition assays elucidated that the complement-mediated killing was not responsible for the inter-individual heterogeneity in either isolate. Subsequently, using MALDI-TOF mass spectrometry on plasmas of 25 healthy individuals, we identified several small molecules including gangliosides, pediocins, or saponins as candidates that showed negative correlation between peak intensities and colony forming units of the test bacteria. This is the first study to demonstrate the inter-individual heterogeneity of constitutive innate humoral bactericidal function quantitatively and that the heterogeneity can be independent of antibody or the complement system.

The African introgression of Murciano Granadina goats has a Moroccan origin and displays remarkable levels of inter-individual variability.

There is evidence that Murciano Granadina (MG), the most important caprine dairy breed in Spain, has been introgressed by African goats, but the precise geographic origin of such introgression has not been identified yet. Moreover, an accurate estimate of the magnitude of this African introgression is lacking, since current estimates are based on small numbers of sampled individuals. The aim of our work was to tackle these two issues by genotyping 500 MG goats with the Goat SNP50 BeadChip and comparing their genotypes with those of reference populations from Spain (Bermeya), France (Saanen), Morocco (Barcha, Draa, Ghazalia, Noire de Atlas, Nord, Moroccan), Egypt (Barki, Oasis, Saidi), Algeria (Arabia, Makatia, M'Zabite, Kabyle), Tunisia (Tunisian native breeds) and Sudan (Desert, Nilotic, Taggar). The population of 500 MG goats was subdivided into 10 datasets of 50 individuals to ensure that sample sizes of the target (MG) and reference populations are balanced. Performance of an unsupervised ADMIXTURE analysis demonstrated that MG goats have a North African ancestry, with an average proportion of 4.4 ± 2.3%. Next, we did a supervised ADMIXTURE analysis that revealed that the Moroccan genetic component reaches a proportion of 4.01 ± 3.9% in MG goats, while the Algerian (0.001 ± 0.001%), Egyptian (0.2 ± 0.1%), Sudanese (0.1 ± 0.1%) and Tunisian (0.3 ± 0.4%) components are present in extremely small proportions. The historical circumstances of this introgression event are currently unknown, but several plausible scenarios are outlined. Moreover, our results show considerable inter-individual heterogeneity regarding the magnitude of the Moroccan introgression of MG goats (0%- 12% depending on the MG data set under analysis). This result implies that reliable estimates about the introgression of autochthonous livestock by exotic breeds can only be obtained by extensively sampling target populations.

Common protein networks for various drug regimens of major depression are associated with complement and immunity.

Major depressive disorder (MDD) can present a variety of clinical presentations and has high inter-individual heterogeneity. Multiple studies have suggested various subtype models related to symptoms, etiology, sex, and treatment response. Employing different regimens is common when treating MDD, and identifying effective therapeutics requires time. Frequent treatment attempts and failures can lead to a diagnosis of treatment resistance, and the heterogeneity of treatment responses among individuals makes it difficult to understand and interpret the biological mechanisms underlying MDD. This study explored the differentially expressed proteins and commonly altered protein networks across drug treatments by comparing the serum proteomes of patients with MDD treated with drug regimens (T-MDD, n = 20) and untreated patients (NT-MDD, n = 20). Differentially expressed proteins were profiled in non-drug-treated and drug-treated patients with depression using liquid chromatography-mass spectrometry. The common protein networks affected by different medications were studied. Of the proteins profiled, 12 were significantly differentially expressed between the T-MDD and NT-MDD groups. Commonly altered proteins and networks of various drug treatments for depression were related to the complement system and immunity. Our results provide information on common biological changes across different pharmacological treatments employed for depression and provide an alternative perspective for improving our understanding of the biological mechanisms of drug response in MDD with great heterogeneity in the background of the disease.

Temporal Dynamics of Stress, Affect, and Abdominal Pain in IBS: Insights from a Clinical Sample

Irritable bowel syndrome (IBS) has a complex aetiology involving biological and psychological alterations. Among others, stress seems to be a relevant factor for IBS symptom onset and exacerbation. Affective changes can be related to symptom severity and stressful experiences and may be valuable for therapeutic purposes. The aim of this study was to examine temporal dynamics of affect, stress, and symptom severity (specifically abdominal pain) in a sample of IBS patients. Thirty-two outpatients kept a diary with a set of short questionnaires (Affect scale, Symptom severity scale, and Daily stress measure) once a day, in the evening, for 14 days. Abdominal pain was modeled as a function of between-person, concurrent and lagged within-person effect of stress and affect controlling for autoregressive pain effects. Positive and negative affect exhibited concurrent effects on abdominal pain while stress did not. Daily variation in positive affect was associated with a decrease in pain while the opposite was true for negative affect. Positive and negative affect models explained over 40% of the variation in daily abdominal pain. Even though the models had a good fit, the amount of variance explained by positive and negative affect alone was relatively small (~7%) with high interindividual heterogeneity. It seems that day-to-day stress variations do not have a direct impact on abdominal pain, while affective dynamics appear closely related to pain variations.

Dissecting Heterogeneity in Functional Network Connectivity Aberrations in Antipsychotic Medication-Naïve First Episode Psychosis Patients - A Normative Modeling Study.

While there is a general consensus that functional connectome pathology is a key mechanism underlying psychosis spectrum disorders, the literature is plagued with inconsistencies and translation into clinical practice is non-existent. This is perhaps because group-level findings may not be accurate reflections of pathology at the individual patient level. To characterize inter-individual heterogeneity in functional networks and investigate if normative values can be leveraged to identify biologically less heterogeneous subgroups of patients. We used data collected in a case-control study conducted at the University of Alabama at Birmingham (UAB). We recruited antipsychotic medication-naïve first-episode psychosis patients from UAB outpatient, inpatient, and emergency room settings. Individual-level patterns of deviations from a normative reference range in resting-state functional networks using the Yeo-17 atlas for parcellations. Statistical analyses included 108 medication-naïve first-episode psychosis patients. We found that there is a high level of inter-individual heterogeneity in resting-state network connectivity deviations from the normative reference range. Interestingly 48% of patients did not have any functional connectivity deviations, and no more than 11.1% of patients shared functional deviations between the same regions of interest. In a post hoc analysis, we grouped patients based on deviations into four theoretically possible groups. We discovered that all four groups do exist in our experimental data and showed that subgroups based on deviation profiles were significantly less heterogeneous compared to the overall group (positive deviation group: z= -2.88, p = 0.002; negative deviation group: z= -3.36, p<0.001). Our findings experimentally demonstrate that there is a high level of inter-individual heterogeneity in resting-state network pathology in first-episode psychosis patients which support the idea that group-level findings are not accurate reflections of pathology at the individual level. We also demonstrated that normative functional connectivity deviations may have utility for identifying biologically less heterogeneous subgroups of patients, even though they are not distinguishable clinically. Our findings constitute a significant step towards making precision psychiatry a reality, where patients are selected for treatments based on their individual biological characteristics. Question: How heterogeneous is individual-level resting-state functional network pathology in patients suffering from a first psychotic episode? Can normative reference values in functional network connectivity be leveraged to identify biologically more homogenous subgroups of patients?Findings: We report that functional network pathology is highly heterogeneous, with no more than 11% of patients sharing functional deviations between the same regions of interest.Meaning: Normative modeling is a tool that can map individual neurobiological differences and enables the classification of a clinically heterogenous patient group into subgroups that are neurobiologically less heterogenous.

Heterogeneity of hepatocellular carcinoma that responds differently to combination therapy with TACE and Sorafenib as determined by digital spatial gene expression profiling.

The combination of Sorafenib and transcatheter arterial chemoembolization (TACE) exhibits limited efficacy in the treatment of certain advanced hepatocellular carcinomas (HCC), and the molecular mechanisms underlying resistance to this combination remain unclear. This study aims to underscore the distinctive contribution of GeoMx DSP technology in elucidating the molecular intricacies of HCC resistance to the Sorafenib and TACE combination. Patients with advanced HCC during the waiting period before liver transplantation were classified into sensitive and resistant groups based on their response to Sorafenib and TACE combination therapy. Employing GeoMx DSP technology for comprehensive gene expression profiling, we identified pivotal molecular targets linked to resistance against combination therapy. The investigation scrutinized intra-tumoral and inter-individual variances, unveiling a spectrum of crucial molecular targets, such as PLG, PLVAP, immunoglobulin genes, ORM1, and NR4A1, among others. Additionally, we explored signaling pathways associated with treatment responsiveness, including the PPAR signaling pathway. Notably, we emphasized the significance of the immune microenvironment characterized by heightened SPP1 expression in HCC resistance to combination therapy. In the resistant group, SPP1+ tumor-associated macrophage (TAM) infiltration was notably pronounced (p = 0.037), while T-cell depletion showed a mitigated presence (p = 0.013). The study reveals intra- and inter-individual heterogeneity in HCC that is differentially responsive to the combination of Sorafenib and TACE, highlighting multiple key molecular targets associated with treatment resistance. The immune microenvironment is important, and in particular, SPP1+ TAM infiltration may play a key role. Meanwhile, the introduction of immunotherapy in patients resistant to combination therapy may lead to positive results.

W64 - Nondrug Reward and Recovery From Addiction: Socio-Spatial Contexts, Interindividual Heterogeneity, and Change Over Time

W64 - Nondrug Reward and Recovery From Addiction: Socio-Spatial Contexts, Interindividual Heterogeneity, and Change Over Time

Population clustering of structural brain aging and its association with brain development.

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Utility of plasma anti-gSG6-P1 IgG levels in determining changes in Anopheles gambiae bite rates in a rural area of Cameroon

The applicability of the specific human IgG antibody response to Anopheles gambiae salivary Gland Protein-6 peptide 1 (gSG6-P1 salivary peptide) as a biomarker able to distinguish the level of exposure to mosquito bites according to seasonal variations has not yet been evaluated in Central African regions. The study aimed to provide the first reliable data on the IgG anti-gSG6-P1 response in rural area in Cameroon according to the dry- and rainy-season. Between May and December 2020, dry blood samples were collected from people living in the Bankeng village in the forest area of the Centre region of Cameroon. Malaria infection was determined by thick-blood smear microscopy and multiplex PCR. The level of IgG anti-gSG6-P1 response, was assessed by enzyme-linked immunosorbent assay. Anopheles density and aggressiveness were assessed using human landing catches. The prevalence of malaria infection remains significantly higher in the rainy season than in the dry season (77.57% vs 61.44%; p = 0.0001). The specific anti-gSG6-P1 IgG response could be detected in individuals exposed to few mosquito bites and showed inter-individual heterogeneity even when living in the same exposure area. In both seasons, the level of anti-gSG6-P1 IgG response was not significantly different between Plasmodium infected and non-infected individuals. Mosquito bites were more aggressive in the rainy season compared to the dry season (human biting rate-HBR of 15.05 b/p/n vs 1.5 b/p/n) where mosquito density was very low. Infected mosquitoes were found only during the rainy season (sporozoite rate = 10.63% and entomological inoculation rate-EIR = 1.42 ib/p/n). The level of IgG anti-gSG6-P1 response was significantly higher in the rainy season and correlated with HBR (p ˂ 0.0001). This study highlights the high heterogeneity of individual’s exposure to the Anopheles gambiae s.l vector bites depending on the transmission season in the same area. These findings reinforce the usefulness of the anti-gSG6-P1 IgG response as an accurate immunological biomarker for detecting individual exposure to Anopheles gambiae s.l. bites during the low risk period of malaria transmission in rural areas and for the differentiating the level of exposure to mosquitoes.

Heterogeneity of morphometric similarity networks in health and schizophrenia.

Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia. Morphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score ≧ than 1.96 was considered supra-normal and a z-score ≦ -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant. At baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences. In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.

Lung microbiome: new insights into bronchiectasis' outcome.

The present treatments for bronchiectasis, which is defined by pathological dilatation of the airways, are confined to symptom relief and minimizing exacerbations. The condition is becoming more common worldwide. Since the disease's pathophysiology is not entirely well understood, developing novel treatments is critically important. The interplay of chronic infection, inflammation, and compromised mucociliary clearance, which results in structural alterations and the emergence of new infection, is most likely responsible for the progression of bronchiectasis. Other than treating bronchiectasis caused by cystic fibrosis, there are no approved treatments. Understanding the involvement of the microbiome in this disease is crucial, the microbiome is defined as the collective genetic material of all bacteria in an environment. In clinical practice, bacteria in the lungs have been studied using cultures; however, in recent years, researchers use next-generation sequencing methods, such as 16S rRNA sequencing. Although the microbiome in bronchiectasis has not been entirely investigated, what is known about it suggests that Haemophilus, Pseudomonas and Streptococcus dominate the lung bacterial ecosystems, they present significant intraindividual stability and interindividual heterogeneity. Pseudomonas and Haemophilus-dominated microbiomes have been linked to more severe diseases and frequent exacerbations, however additional research is required to fully comprehend the role of microbiome in the evolution of bronchiectasis. This review discusses recent findings on the lung microbiota and its association with bronchiectasis.

Plasma calcitonin gene-related peptide levels in idiopathic intracranial hypertension: an exploratory study

BackgroundIdiopathic intracranial hypertension (IIH) is a debilitating condition characterized by increased intracranial pressure often presenting with chronic migraine-like headache. Calcitonin gene-related peptide (CGRP) plays an important pathophysiological role in primary headaches such as migraine, whilst its role in IIH has not yet been established.MethodsThis longitudinal exploratory study included patients with IIH, episodic migraine (EM) in a headache-free interval and healthy controls (HC). Blood samples were collected from a cubital vein and plasma CGRP (pCGRP) levels were measured by standardized ELISA.ResultsA total of 26 patients with IIH (mean age 33.2 years [SD 9.2], 88.5% female, median BMI 34.8 kg/m2 [IQR 30.0–41.4]), 30 patients with EM (mean age 27.6 years [7.5], 66.7% female) and 57 HC (mean age 25.3 years [5.2], 56.1% female) were included. pCGRP levels displayed a wide variation in IIH as well as in EM and HC on a group-level. Within IIH, those with migraine-like headache had significantly higher pCGRP levels than those with non-migraine-like headache (F(2,524) = 84.79; p < 0.001) and headache absence (F(2,524) = 84.79; p < 0.001) throughout the observation period, explaining 14.7% of the variance in pCGRP levels. CGRP measurements showed strong intraindividual agreement in IIH (ICC 0.993, 95% CI 0.987–0.996, p < 0.001). No association was found between pCGRP levels and ophthalmological parameters.ConclusionsAlthough interindividual heterogeneity of pCGRP levels is generally high, migraine-like headache seems to be associated with higher pCGRP levels. CGRP may play a role in the headache pathophysiology at least in a subgroup of IIH.