Autism Research: An Objective Quantitative Review of Progress and Focus Between 1994 and 2015

Gut microbiota and autism spectrum disorders: where do we stand?

BACKGROUND

Children with autism spectrum disorder (ASD) often have digestive problems and microbial imbalances in their guts, suggesting that these conditions may play a role in the development of the disorder. Scopus-based research on the gut microbiota and ASD was examined in this bibliometric analysis to shed light on the current state of research and identify potential hotspots for future work in this area.

METHODS

We searched documents from the Scopus database and reference citation analysis to collect published data on the gut microbiota and ASD from 2003 to 2022. The downloaded document records were exported to VOSviewer v.1.6.19 to examine and visualize the collaboration between countries and determine the research hotspots.

RESULTS

The search yielded 958 articles specifically dedicated to gut microbiota and ASD. The number of publications in this field increased rapidly after 2013, with a peak in 2022. The United States (n = 267; 27.87%) was the most active country, followed by China (n = 171; 17.85%) and Italy (n = 96; 10.02). International collaboration was observed, with the USA playing a central role. University College Cork, Ireland, was the most productive institution (n = 24; 2.51%). The National Natural Science Foundation of China was the most active funding agency (n = 76; 7.93%). Nutrients journal had the highest number of publications (n = 28; 2.92%). The articles related to gut microbiota and ASD were highly cited, with an h-index of 108. The research themes identified focused on the modulation of gut microbiota as a potential therapy for children with ASD and gut-brain axis dysfunction in ASD.

CONCLUSIONS

In recent years, the study of gut microbiota and its association with ASD has garnered considerable interest as an emergent field of study. The results of this study substantially enhance our current understanding of the knowledge landscape in this field and illuminate potential avenues for future research. It is essential to emphasize the significance of devoting more resources to the newest and most promising research areas, such as investigating the potential therapeutic benefits of modulating the intestinal microbiota in children with ASD. This research has enormous potential and merits intensified focus and investigation.

Value co-creation in business-to-business context: A bibliometric analysis using HistCite and VOS viewer

Abstract purpose

Value co-creation (VCC) recently displayed a significant increase in the frequency of publications in business studies and social sciences. Our study objects to explore the current state of VCC research in the business-to-business (B2B) context, principally in the marketing field.

Research design approach and methodology

This research article extracted research papers on VCC in the B2B context published in the last two decades through the Web of Science (WoS). Initially, we applied HistCite to determine the research dynamics of VCC articles and then VOS viewer to conduct bibliographic coupling and cartographic analysis. Furthermore, we found the most co-occurred keywords in the abstracts, titles, and keywords.

Findings

Our research explored that the United Kingdom was the most important country with 27 publications and 594 citations. Aarikka-Stenroos L was the most influential author, among his research is a systematic review which revealed that scholars of B2B journals adopted the term business "ecosystem" and studied the implications of ecosystem perspective in business and innovation networks and received the most citations. Industrial Marketing Management (IMM) was the most influential journal because it published 8 of the 10 most cited articles. One hundred and six out of 121 publications were in Business research and seventy-six were in management area, which made it the most hot and critical research area. Lappeenranta University was the most essential organization in VCC research based on the most records published and second-highest citations.

Research limitations/implications and future research

Four research streams have emerged which indicate the prominent role of VCC in the B2B context (1) VCC and relationships, (2) VCC and organizational capabilities, (3) VCC and actors' engagement at various platforms, and (4) VCC and processes. Our research paper provided a base for conceptualizing publications related to business, management, operations research management science, and social sciences interdisciplinary on VCC in the B2B context. Content analysis has revealed that research work on VCC in the B2B context is at an early stage in the marketing arena. Along with bringing some sort of consensus regarding researchers' opinion toward the nature and modality of VCC literature and process in the B2B context, we urge future research to focus on how relationships and their precursors can be efficiently utilized to co-create and enhance value within B2B interactions. We also request future research to focus on making the VCC process sustainable and viable both on a time and economical basis.

Practical implications

Organizations can involve customers and producers to work jointly to co-create value for their goods and services with negligible cost to achieve higher market shares and a competitive edge over rivals.

Originality/value

This might be the first bibliometric study conducted on VCC in the B2B context (there are some Bibliometric VCC publications, but they are not B2B-specific, our research is the first Bibliometric study conducted on VCC in the B2B context) in the marketing field and can expose novel avenues for future research.

Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify Its "Epidemic Rates"

In the last decade, Autism has broadened and often shifted its diagnostics criteria, allowing several neuropsychiatric and neurological disorders of known etiology. This has resulted in a highly heterogeneous spectrum with apparent exponential rates in prevalence. I ask if it is possible to leverage existing genetic information about those disorders making up Autism today and use it to stratify this spectrum. To that end, I combine genes linked to Autism in the SFARI database and genomic information from the DisGeNET portal on 25 diseases, inclusive of non-neurological ones. I use the GTEx data on genes’ expression on 54 human tissues and ask if there are overlapping genes across those associated to these diseases and those from SFARI-Autism. I find a compact set of genes across all brain-disorders which express highly in tissues fundamental for somatic-sensory-motor function, self-regulation, memory, and cognition. Then, I offer a new stratification that provides a distance-based orderly clustering into possible Autism subtypes, amenable to design personalized targeted therapies within the framework of Precision Medicine. I conclude that viewing Autism through this physiological (Precision) lens, rather than viewing it exclusively from a psychological behavioral construct, may make it a more manageable condition and dispel the Autism epidemic myth.

Brain and Language Associations in Autism Spectrum Disorder: A Scoping Review

Examining brain and behaviour associations for language in autism spectrum disorder (ASD) may bring us closer to identifying neural profiles that are unique to a subgroup of individuals with ASD identified as language impaired (e.g. ASD LI+). We conducted a scoping review to examine brain regions that are associated with language performance in ASD. Further, we examined methodological differences across studies in how language ability was characterized and what neuroimaging methods were used to explore brain regions. Seventeen studies met inclusion criteria. Brain regions specific to ASD LI+ groups were found, however inconsistencies in brain and language associations were evident across study findings. Participant age, age-appropriate language scores, and neuroimaging methods likely contributed to differences in associations found.

A Bibliometric Insight of Genetic Factors in ASD: Emerging Trends and New Developments

Autism spectrum disorder (ASD) cases have increased rapidly in recent decades, which is associated with various genetic abnormalities. To provide a better understanding of the genetic factors in ASD, we assessed the global scientific output of the related studies. A total of 2944 studies published between 1997 and 2018 were included by systematic retrieval from the Web of Science (WoS) database, whose scientific landscapes were drawn and the tendencies and research frontiers were explored through bibliometric methods. The United States has been acting as a leading explorer of the field worldwide in recent years. The rapid development of high-throughput technologies and bioinformatics transferred the research method from the traditional classic method to a big data-based pipeline. As a consequence, the focused research area and tendency were also changed, as the contribution of de novo mutations in ASD has been a research hotspot in the past several years and probably will remain one into the near future, which is consistent with the current opinions of the major etiology of ASD. Therefore, more attention and financial support should be paid to the deciphering of the de novo mutations in ASD. Meanwhile, the effective cooperation of multi-research centers and scientists in different fields should be advocated in the next step of scientific research undertaken.

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis.

Hidden Aspects of the Research ADOS Are Bound to Affect Autism Science

The research-grade Autism Diagnostic Observational Schedule (ADOS) is a broadly used instrument that informs and steers much of the science of autism. Despite its broad use, little is known about the empirical variability inherently present in the scores of the ADOS scale or their appropriateness to define change and its rate, to repeatedly use this test to characterize neurodevelopmental trajectories. Here we examine the empirical distributions of research-grade ADOS scores from 1324 records in a cross-section of the population comprising participants with autism between five and 65 years of age. We find that these empirical distributions violate the theoretical requirements of normality and homogeneous variance, essential for independence between bias and sensitivity. Further, we assess a subset of 52 typical controls versus those with autism and find a lack of proper elements to characterize neurodevelopmental trajectories in a coping nervous system changing at nonuniform, nonlinear rates. Repeating the assessments over four visits in a subset of the participants with autism for whom verbal criteria retained the same appropriate ADOS modules over the time span of the four visits reveals that switching the clinician changes the cutoff scores and consequently influences the diagnosis, despite maintaining fidelity in the same test's modules, room conditions, and tasks' fluidity per visit. Given the changes in probability distribution shape and dispersion of these ADOS scores, the lack of appropriate metric spaces to define similarity measures to characterize change and the impact that these elements have on sensitivity-bias codependencies and on longitudinal tracking of autism, we invite a discussion on readjusting the use of this test for scientific purposes.

Multi-Scale Coordination of Distinctive Movement Patterns During Embodied Interaction Between Adults With High-Functioning Autism and Neurotypicals

Autism Spectrum Disorder (ASD) can be understood as a social interaction disorder. This requires researchers to take a “second-person” stance and to use experimental setups based on bidirectional interactions. The present work offers a quantitative description of movement patterns exhibited during computer-mediated real-time sensorimotor interaction in 10 dyads of adult participants, each consisting of one control individual (CTRL) and one individual with high-functioning autism (HFA). We applied time-series analyses to their movements and found two main results. First, multi-scale coordination between participants was present. Second, despite this dyadic alignment and our previous finding that individuals with HFA can be equally sensitive to the other’s presence, individuals’ movements differed in style: in contrast to CTRLs, HFA participants appeared less inclined to sustain mutual interaction and instead explored the virtual environment more generally. This finding is consistent with social motivation deficit accounts of ASD, as well as with hypersensitivity-motivated avoidance of overstimulation. Our research demonstrates the utility of time series analyses for the second-person stance and complements previous work focused on non-dynamical and performance-based variables.