Association of Loneliness and Wisdom With Gut Microbial Diversity and Composition: An Exploratory Study

Salivary microbiota composition before and after use of proton pump inhibitors in patients with laryngopharyngeal reflux: a self-control study

BACKGROUND

Issues associated with proton pump inhibitor (PPI) usage have been documented. PPIs affect the gastrointestinal microbiome, as well as the saliva microbiota of healthy individuals. However, the alterations in the saliva microbiota of laryngopharyngeal reflux (LPR) patients remain unclear. This study aims to examine the composition of saliva microbiota in LPR patients before and after PPI usage through a self-controlled study.

METHODS

Thirty-two adult LPR patients participated in the study. Saliva samples were collected before and after an 8-week regimen of twice-daily administration of 20-mg esomeprazole. The impact of PPI administration on bacterial communities was assessed using 16 S rRNA gene sequencing. The functional and metabolic changes in saliva microbial communities after PPI usage were analyzed using PICRUSt2 based on our 16 S rRNA gene sequencing results.

RESULTS

The alpha diversity within the salivary microbiota, as measured by the PD-whole-tree index, exhibited a significant difference between samples collected before and after PPI application (P = 0.038). Additionally, PCoA analysis of unweighted UniFrac distances (beta diversity) revealed distinct separation of saliva sample microbiota structures before and after PPI application in LPR patients, with statistical significance (Adonis test, R2 = 0.063, P< 0.010). Taxon-based analysis indicated that PPI administration increased the abundance of Epsilonproteobacteria, Campylobacterales, Campylobacteraceae, Campylobacter, and Campylobacter_gracilis, while reducing the abundance of Lactobacillaceae and Lactobacillus in salivary samples ( P< 0.050). Using LEfSe to compare bacterial abundances, Bacillaceae and Anoxybacillus were found to be enriched before PPI usage in LPR patients. Furthermore, the proportion of genes responsible for indole alkaloid biosynthesis in the salivary microbiota of LPR patients significantly increased after PPI therapy (P< 0.050).

CONCLUSIONS

These findings indicate that PPIs induce alterations in the salivary microbiota of LPR patients.

CHINESE CLINICAL TRIAL REGISTRY

No. ChiCTR2300067507. Registered on January 10,2023 retrospectively.

LEVEL OF EVIDENCE: 4

A New Paradigm for High-dimensional Data: Distance-Based Semiparametric Feature Aggregation Framework via Between-Subject Attributes

This article proposes a distance-based framework incentivized by the paradigm shift towards feature aggregation for high-dimensional data, which does not rely on the sparse-feature assumption or the permutation-based inference. Focusing on distance-based outcomes that preserve information without truncating any features, a class of semiparametric regression has been developed, which encapsulates multiple sources of high-dimensional variables using pairwise outcomes of between-subject attributes. Further, we propose a strategy to address the interlocking correlations among pairs via the U-statistics-based estimating equations (UGEE), which correspond to their unique efficient influence function (EIF). Hence, the resulting semiparametric estimators are robust to distributional misspecification while enjoying root-n consistency and asymptotic optimality to facilitate inference. In essence, the proposed approach not only circumvents information loss due to feature selection but also improves the model's interpretability and computational feasibility. Simulation studies and applications to the human microbiome and wearables data are provided, where the feature dimensions are tens of thousands.

Deciphering the 'gut-brain axis' through microbiome diversity

Incentivised by breakthroughs and data generated by the high-throughput sequencing technology, this paper proposes a distance-based framework to fulfil the emerging needs in elucidating insights from the high-dimensional microbiome data in psychiatric studies. By shifting focus from traditional methods that focus on the observations from each subject to the between-subject attributes that aggregate two or more subjects' entire feature vectors, the described approach revolutionises the conventional prescription for high-dimensional observations via microbiome diversity. To this end, we enrich the classical generalised linear models to articulate the multivariable regression relationship between distance-based variables. We also discuss a robust and computationally feasible semiparametric inference technique. Benefitting from the latest advances in the semiparametric efficiency theory for such attributes, the proposed estimators enjoy robustness and good asymptotic properties that guarantee sensitivity in detecting signals between clinical outcomes and microbiome diversity. It offers a readily implementable and easily interpretable solution for deciphering the gut-brain axis in mental health research.

Review of Major Social Determinants of Health in Schizophrenia-Spectrum Psychotic Disorders: III. Biology

BACKGROUND

Social determinants of health (SDoHs) are nonmedical factors that significantly impact health and longevity. We found no published reviews on the biology of SDoHs in schizophrenia-spectrum psychotic disorders (SSPD).

STUDY DESIGN

We present an overview of pathophysiological mechanisms and neurobiological processes plausibly involved in the effects of major SDoHs on clinical outcomes in SSPD.

STUDY RESULTS

This review of the biology of SDoHs focuses on early-life adversities, poverty, social disconnection, discrimination including racism, migration, disadvantaged neighborhoods, and food insecurity. These factors interact with psychological and biological factors to increase the risk and worsen the course and prognosis of schizophrenia. Published studies on the topic are limited by cross-sectional design, variable clinical and biomarker assessments, heterogeneous methods, and a lack of control for confounding variables. Drawing on preclinical and clinical studies, we propose a biological framework to consider the likely pathogenesis. Putative systemic pathophysiological processes include epigenetics, allostatic load, accelerated aging with inflammation (inflammaging), and the microbiome. These processes affect neural structures, brain function, neurochemistry, and neuroplasticity, impacting the development of psychosis, quality of life, cognitive impairment, physical comorbidities, and premature mortality. Our model provides a framework for research that could lead to developing specific strategies for prevention and treatment of the risk factors and biological processes, thereby improving the quality of life and increasing the longevity of people with SSPD.

CONCLUSIONS

Biology of SDoHs in SSPD is an exciting area of research that points to innovative multidisciplinary team science for improving the course and prognosis of these serious psychiatric disorders.

Forging the microbiome to help us live long and prosper

Aging is often accompanied by an increased risk of an array of diseases spanning the cardiovascular, nervous, and immune systems, among others. Despite remarkable progress in understanding the cellular and molecular mechanisms involved in aging, the role of the microbiome remains understudied. In this Essay, we highlight recent progress towards understanding if and how the microbiome contributes to aging and age-associated diseases. Furthermore, we discuss the need to consider sexually dimorphic phenotypes in the context of aging and the microbiome. We also highlight the broad implications for this emerging area of interdisciplinary research to address long-standing questions about host-microbiome interactions across the life span.

The Microbiome and Mental Health Across the Lifespan

INTRODUCTION

The combined genetic material of the microorganisms in the human body, known as the microbiome, is being increasingly recognized as a major determinant of human health and disease. Although located predominantly on mucosal surfaces, these microorganisms have profound effects on brain functioning through the gut-brain axis.

METHOD

The content of the chapter is based on a study group session at the annual meeting of the American College of Neuropsychopharmacology (ACNP). The objective was to discuss the emerging relationship between the human microbiome and mental health as relevant to ACNP's interests in developing and evaluating novel neuropsychiatric treatment strategies. The focus is on specific brain disorders, such as schizophrenia, substance use, and Alzheimer's disease, as well as on broader clinical issues such as suicidality, loneliness and wisdom in old age, and longevity.

RESULTS

Studies of schizophrenia indicate that the microbiome of individuals with this disorder differs from that of non-psychiatric comparison groups in terms of diversity and composition. Differences are also found in microbial metabolic pathways. An early study in substance use disorders found that individuals with this disorder have lower levels of beta diversity in their oral microbiome than a comparison group. This measure, along with others, was used to distinguish individuals with substance use disorders from controls. In terms of suicidality, there is preliminary evidence that persons who have made a suicide attempt differ from psychiatric and non-psychiatric comparison groups in measures of beta diversity. Exploratory studies in Alzheimer's disease indicate that gut microbes may contribute to disease pathogenesis by regulating innate immunity and neuroinflammation and thus influencing brain function. In another study looking at the microbiome in older adults, positive associations were found between wisdom and alpha diversity and negative associations with subjective loneliness. In other studies of older adults, here with a focus on longevity, individuals with healthy aging and unusually long lives had an abundance of specific microorganisms which distinguished them from other individuals.

DISCUSSION

Future studies would benefit from standardizing methods of sample collection, processing, and analysis. There is also a need for the standardized collection of relevant demographic and clinical data, including diet, medications, cigarette smoking, and other potentially confounding factors. While still in its infancy, research to date indicates a role for the microbiome in mental health disorders and conditions. Interventions are available which can modulate the microbiome and lead to clinical improvements. These include microbiome-altering medications as well as probiotic microorganisms capable of modulating the inflammation in the brain through the gut-brain axis. This research holds great promise in terms of developing new methods for the prevention and treatment of a range of human brain disorders.

A systematic review of loneliness and social isolation among Hispanic/Latinx older adults in the United States

Loneliness and social isolation are growing public health problems in older adults, associated with physical and mental comorbidity and increased mortality. In the United States, Hispanic/Latinx individuals constitute the largest racial/ethnic minority. Studies retrieved from PsycInfo, Embase, and PubMed were examined. The initial search yielded 1476 publications. Using the updated PRISMA Flow guidelines, a total of 17 studies met our review criteria. Eight studies assessed loneliness, six evaluated social isolation, and three investigated both. The reports varied in the details of methodology, preventing meta-analyses. Differences in the experience of loneliness and social isolation between Hispanic/Latinx and White adults are not consistent. Of the three studies of loneliness or social isolation among Hispanic/Latinx groups of different national origins, two reported significant differences. Loneliness was associated with greater overall comorbidity, but two studies found higher risk of metabolic and cardiovascular disorders in Hispanic/Latinx with loneliness. Social isolation was generally associated with worse physical health, being older, male, and unmarried, and having lower education and income, and more smoking, along with frailty and cognitive impairment. We make specific suggestions for future research on loneliness and social isolation in Hispanic/Latinx adults and offer guidelines for clinical management.

Abbreviated San Diego Wisdom Scale (SD-WISE-7) and Jeste-Thomas Wisdom Index (JTWI)

OBJECTIVES

Wisdom is a personality trait comprising seven components: self-reflection, pro-social behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality. Wisdom, a potentially modifiable trait, is strongly associated with well-being. We have published a validated 28-item San Diego Wisdom Scale, the SD-WISE-28. Brief scales are necessary for use in large population-based studies and in clinical practice. The present study aimed to create an abbreviated 7-item version of the SD-WISE.

METHOD

Participants included 2093 people, aged 20-82 years, recruited and surveyed through the online crowdsourcing platform Amazon Mechanical Turk. The participants' mean age was 46 years, with 55% women. Participants completed the SD-WISE-28 as well as validation scales for various positive and negative constructs. Psychometric analyses (factor analysis and item response theory) were used to select one item from each of the seven SD-WISE-28 subscales.

RESULTS

We selected a combination of items that produced acceptable unidimensional model fit and good reliability (ω = 0.74). Item statistics suggested that all seven items were strong indicators of wisdom, although the association was weakest for spirituality. Analyses indicated that the 28-item and 7-item SD-WISE are both very highly correlated (r = 0.92) and produce a nearly identical pattern of correlations with demographic and validity variables.

CONCLUSION

The SD-WISE-7, and its derived Jeste-Thomas Wisdom Index (JTWI) score, balances reliability and brevity for research applications.

Stressor-Specific Microbiota Intervention

To date, mental disorders are diagnosed and treated by the subjective judgment of psychiatrists based on diagnostic criteria and treatment guidelines, respectively. Mental disorders are heterogeneous illnesses with a substantial treatment-refractory rate. Thus, there is a great need for novel treatment approaches. This article proposes a treatment approach centered on the concept of the gut–brain axis. There is mounting evidence indicating an association between stressors, microbiota, microglia, and mental disorders. Stressors might facilitate dysbiosis, inflammation, and the occurrence of mental disorders. This novel treatment approach is based on the idea that stressor types instead of the heterogeneous psychiatric diagnosis might be closer to the neurobiological underpinnings of mental disorders. First of all, patients with treatment-resistant mental disorders will be asked to describe their major stressors. Then, clinicians will calculate the total threat score and the total deprivation score. Subsequently, treatment tailored to the major stressor type will be administered to restore a healthy gut microbiome. Presumably, treatment will be aimed at increasing microbiota diversity in those who mainly have deprivation stressors and boosting Actinobacteria in those who have mainly threat stressors. Large-scale clinical trials are warranted to test this hypothetical approach.

Partial least squares regression and principal component analysis: similarity and differences between two popular variable reduction approaches

In many statistical applications, composite variables are constructed to reduce the number of variables and improve the performances of statistical analyses of these variables, especially when some of the variables are highly correlated. Principal component analysis (PCA) and factor analysis (FA) are generally used for such purposes. If the variables are used as explanatory or independent variables in linear regression analysis, partial least squares (PLS) regression is a better alternative. Unlike PCA and FA, PLS creates composite variables by also taking into account the response, or dependent variable, so that they have higher correlations with the response than composites from their PCA and FA counterparts. In this report, we provide an introduction to this useful approach and illustrate it with data from a real study.

Methodology Considerations in Studying Mental Health, Sleep Quality, and Biopsychosocial Determinants Among Chinese and Korean Americans During the COVID-19 Pandemic

Asians are one of the fastest-growing racial groups in the United States. The mental health of Asian Americans, particularly regarding depression and anxiety, needs significant attention. Various biopsychosocial factors interact to influence the risks of depression, anxiety, and sleep quality among Asian Americans. Currently, multiple methodological issues exist in the research of Asian Americans, such as limited data collection using Asian languages and inconsistent reporting of race and ethnicity data, which may be lacking entirely. All these methodological issues in research may account for the seemingly low prevalence rates of mental health problems among Asian Americans. In our study on mental health and sleep quality among Chinese and Korean Americans, we adopted multiple data collection strategies during the COVID-19 pandemic, including using culturally adaptive and validated measures as well as operating culture-sensitive procedures in the recruitment and data collection. The successful use of these strategies could promote early detection and personalized treatment of depression, anxiety, and sleep disturbance among Asian Americans. These strategies would further improve health care service use in this population.

International Registered Report Identifier IRRID

RR2-10.1136/bmjopen-2020-047281.

Compassion toward others and self-compassion predict mental and physical well-being: a 5-year longitudinal study of 1090 community-dwelling adults across the lifespan

There is growing interest in the role of compassion in promoting health and well-being, with cross-sectional data showing an inverse correlation with loneliness. This is the first longitudinal study examining both compassion toward others (CTO) and compassion toward self (CTS) as predictors of mental and physical health outcomes including loneliness, across adult lifespan. We followed 552 women and 538 men in San Diego County for up to 7.5 (mean 4.8 and SD 2.2) years, using validated rating scales for CTO, CTS, and loneliness. Linear mixed-effects models were employed to examine age- and sex-related trajectories of CTO and CTS over time. Linear regression models were used to evaluate baseline and longitudinal relationships of CTO and CTS with mental well-being, physical well-being, and loneliness. CTS and CTO were weakly intercorrelated. Women had higher baseline CTO than men. While CTO was stable over time and across the lifespan, CTS scores had an inverse U-shaped relationship with age, peaking around age 77. There were significant baseline × slope interactions of both CTO and CTS predicting improvements in physical well-being in adults <60 years old. Increases in CTO and CTS predicted improvements in mental well-being. Higher baseline CTO and CTS as well as increases in CTO and CTS scores predicted lower loneliness scores at follow-up. Thus, CTO and CTS were associated with better mental well-being and loneliness across the adult lifespan, and physical well-being in younger adults, and are promising targets for interventions to improve health outcomes.

Crocodile Gut Microbiome Is a Potential Source of Novel Bioactive Molecules

Here, it is proposed that the crocodile gut microbiome is a valuable biomaterials resource to counter threats posed by environmental and infectious hazards to the existence of Homo sapiens.