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Nevin Manimala Statistics

Functional and molecular characterization of suicidality factors using phenotypic and genome-wide data

Mol Psychiatry. 2023 Jan 6. doi: 10.1038/s41380-022-01929-5. Online ahead of print.

ABSTRACT

Genome-wide association studies (GWAS) of suicidal thoughts and behaviors support the existence of genetic contributions. Continuous measures of psychiatric disorder symptom severity can sometimes model polygenic risk better than binarized definitions. We compared two severity measures of suicidal thoughts and behaviors at the molecular and functional levels using genome-wide data. We used summary association data from GWAS of four traits analyzed in 122,935 individuals of European ancestry: thought life was not worth living (TLNWL), thoughts of self-harm, actual self-harm, and attempted suicide. A new trait for suicidal thoughts and behaviors was constructed first, phenotypically, by aggregating the previous four traits (termed “suicidality”) and second, genetically, by using genomic structural equation modeling (gSEM; termed S-factor). Suicidality and S-factor were compared using SNP-heritability (h2) estimates, genetic correlation (rg), partitioned h2, effect size distribution, transcriptomic correlations (ρGE) in the brain, and cross-population polygenic scoring (PGS). The S-factor had good model fit (χ2 = 0.21, AIC = 16.21, CFI = 1.00, SRMR = 0.024). Suicidality (h2 = 7.6%) had higher h2 than the S-factor (h2 = 2.54, Pdiff = 4.78 × 10-13). Although the S-factor had a larger number of non-null susceptibility loci (πc = 0.010), these loci had small effect sizes compared to those influencing suicidality (πc = 0.005, Pdiff = 0.045). The h2 of both traits was enriched for conserved biological pathways. The rg and ρGE support highly overlapping genetic and transcriptomic features between suicidality and the S-factor. PGS using European-ancestry SNP effect sizes strongly associated with TLNWL in Admixed Americans: Nagelkerke’s R2 = 8.56%, P = 0.009 (PGSsuicidality) and Nagelkerke’s R2 = 7.48%, P = 0.045 (PGSS-factor). An aggregate suicidality phenotype was statistically more heritable than the S-factor across all analyses and may be more informative for future genetic study designs interested in common genetic factors among different suicide related phenotypes.

PMID:36604601 | DOI:10.1038/s41380-022-01929-5

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Nevin Manimala Statistics

The association between early onset of alcohol, smokeless tobacco and marijuana use with adult binge drinking in United States

Sci Rep. 2023 Jan 5;13(1):187. doi: 10.1038/s41598-023-27571-x.

ABSTRACT

Binge drinking is a deadly pattern of excessive alcohol use that is associated with multiple diseases in the United States. To date, little is known about the associations between the early onset of substance use and other factors with the severity of adult binge drinking. The 2018 National Survey on Drug Use and Health data was used to identify binge drinking (binary and in number of days in the past month). Age at onset was categorized into four groups as 1-12, 13-14, 15-17, or beyond 18. Weighted multivariate logistic regression and Poisson regression analyses were performed to examine the associations between early onset of alcohol, smokeless tobacco, and marijuana use with binge drinking. The severity of binge drinking was statistically significantly associated with substance use (4.15 days in a month), early onset of alcohol, smokeless tobacco, and marijuana use (2.15-4.93 days, all p-values < 0.0001), after accounting for the covariates. Past year substance use disorder is strongly associated with binge drinking. The severity of adult binge drinking is significantly associated with early onset of substance use including alcohol, smokeless tobacco, and marijuana. Continued efforts are warranted to improve substance use prevention and treatment tailored for adolescents and youths to prevent development of adult binge drinking.

PMID:36604596 | DOI:10.1038/s41598-023-27571-x

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Nevin Manimala Statistics

Analysis of functional connectivity in depression based on a weighted hyper-network method

J Neural Eng. 2023 Jan 5. doi: 10.1088/1741-2552/acb088. Online ahead of print.

ABSTRACT

OBJECTIVE: Brain connectivity network is a vital tool to reveal the interaction between different brain regions. Currently, most functional connectivety methods can only capture pairs of information to construct brain networks which ignored the high-order correlations between brain regions.

APPROACH: Therefore, this study proposed a weighted connectivity hyper-network based on resting-state EEG data, and then applied to depression identification and analysis. The hyper-network model was builed based on least absolute shrinkage and selection operator (LASSO) sparse regression method to effectively represent the higher-order relationships of brain regions. On this basis, by integrating the correlation-based weighted hyper-edge information, the weighted hyper-network is constructed, and the topological features of the network are extracted for classification.

MAIN RESULTS: The experimental results obtained an optimal accuracy compared to the traditional coupling methods. The statistical results on network metrics proved that there were significant differences between depressive patients (DP) and normal controls (NC). In addition, some brain regions and electrodes were found and discussed to highly correlate with depression by analyzing of the critical nodes and hyper-edges.

SIGNIFICANCE: These may help discover disease-related biomarkers important for depression diagnosis.

PMID:36603214 | DOI:10.1088/1741-2552/acb088

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Nevin Manimala Statistics

Supervised latent Dirichlet allocation with covariates: A Bayesian structural and measurement model of text and covariates

Psychol Methods. 2023 Jan 5. doi: 10.1037/met0000541. Online ahead of print.

ABSTRACT

Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently, psychologists have studied relationships between these topics and other psychological measures by using estimates of the topics as regression predictors along with other manifest variables. While similar two-stage approaches involving estimated latent variables are known to yield biased estimates and incorrect standard errors, two-stage topic modeling approaches have received limited statistical study and, as we show, are subject to the same problems. To address these problems, we proposed a novel statistical model-supervised latent Dirichlet allocation with covariates (SLDAX)-that jointly incorporates a latent variable measurement model of text and a structural regression model to allow the latent topics and other manifest variables to serve as predictors of an outcome. Using a simulation study with data characteristics consistent with psychological text data, we found that SLDAX estimates were generally more accurate and more efficient. To illustrate the application of SLDAX and a two-stage approach, we provide an empirical clinical application to compare the application of both the two-stage and SLDAX approaches. Finally, we implemented the SLDAX model in an open-source R package to facilitate its use and further study. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

PMID:36603124 | DOI:10.1037/met0000541

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Nevin Manimala Statistics

Comparison of Aromatherapy with Citrus aurantium and Lavender on Sexual Satisfaction in Breastfeeding Women: A Randomized Controlled Trial

Breastfeed Med. 2023 Jan 5. doi: 10.1089/bfm.2022.0179. Online ahead of print.

ABSTRACT

Objective: The aim of this study was to investigate the effects of aroma of Citrus aurantium and Lavender essence on sexual satisfaction in breastfeeding women. Materials and Methods: This was a double-blind randomized controlled trial that was conducted on 180 breastfeeding women from January to May 2019. The participants were allocated to three groups of Citrus aurantium (n = 60), Lavender (n = 60), and control (n = 60) groups. Two groups of intervention used 2 drops of essential oil, twice a day, for 40 days as inhalation. The control group received almond oil in the same. The sexual satisfaction was evaluated using the Linda Berg’s Sexual Satisfaction Questionnaire before the intervention and 40 days after the intervention started. The data were analyzed using the SPSS statistical software, version 21, and p < 0.05 was considered statistically significant. Results: After the 40 days of intervention, the mean score of sexual satisfaction was significantly higher in the Citrus aurantium and Lavender groups compared with the control group (59.3 ± 11.7, 59.3 ± 11.6 vs. 52.02 ± 11.5, p < 0.001). There was no significant difference between Lavender and Citrus aurantium groups. Conclusions: The results of this study showed that the aroma of Citrus aurantium and Lavender essence could significantly improve the sexual satisfaction of breastfeeding women. Therefore, it is recommended that health care providers should inform the breastfeeding women and advise them to use these interventions for increase of the sexual satisfaction. Trial Registration Number: IRCT20160427027633N3.

PMID:36603110 | DOI:10.1089/bfm.2022.0179

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Nevin Manimala Statistics

The Supplementary Motor Area and Automatic Cognitive Control: Lack of Evidence from Two Neuromodulation Techniques

J Cogn Neurosci. 2022 Dec 28:1-13. doi: 10.1162/jocn_a_01954. Online ahead of print.

ABSTRACT

BACKGROUND: The SMA is fundamental in planning voluntary movements and execution of some cognitive control operations. Specifically, the SMA has been associated to play a dominant role in controlling goal-directed actions as well as those that are highly predicted (i.e., automatic). Yet, the essential contribution of SMA in goal-directed or automatic control of behavior is scarce. Our objective was to test the possible direct role of SMA in automatic and voluntary response inhibition.

METHODS: We separately applied two noninvasive brain stimulation (NIBS) inhibitory techniques over SMA: either continuous theta-burst stimulation using repetitive transcranial magnetic stimulation or transcranial static magnetic field stimulation. Each NIBS technique was performed in a randomized, crossover, sham-controlled design. Before applying NIBS, participants practiced a go/no-go learning task where associations between stimulus and stopping behaviors were created (initiation and inhibition). After applying each NIBS, participants performed a go/no-go task with reversed associations (automatic control) and the stop signal task (voluntary control).

RESULTS: Learning associations between stimuli and response initiation/inhibition was achieved by participants and therefore automatized during training. However, no significant differences between real and sham NIBS were found in either automatic (go/no-go learning task) or voluntary inhibition (stop signal task), with Bayesian statistics providing moderate evidence of absence.

CONCLUSIONS: Our results are compatible with a nondirect involvement of SMA in automatic control of behavior. Further studies are needed to prove a noncausal link between prior neuroimaging findings relative to SMA controlling functions and the observed behavior.

PMID:36603037 | DOI:10.1162/jocn_a_01954

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Nevin Manimala Statistics

Multi-dimensional resilience: A quantitative exploration of disease outcomes and economic, political, and social resilience to the COVID-19 pandemic in six countries

PLoS One. 2023 Jan 5;18(1):e0279894. doi: 10.1371/journal.pone.0279894. eCollection 2023.

ABSTRACT

The COVID-19 pandemic has highlighted a need for better understanding of countries’ vulnerability and resilience to not only pandemics but also disasters, climate change, and other systemic shocks. A comprehensive characterization of vulnerability can inform efforts to improve infrastructure and guide disaster response in the future. In this paper, we propose a data-driven framework for studying countries’ vulnerability and resilience to incident disasters across multiple dimensions of society. To illustrate this methodology, we leverage the rich data landscape surrounding the COVID-19 pandemic to characterize observed resilience for several countries (USA, Brazil, India, Sweden, New Zealand, and Israel) as measured by pandemic impacts across a variety of social, economic, and political domains. We also assess how observed responses and outcomes (i.e., resilience) of the COVID-19 pandemic are associated with pre-pandemic characteristics or vulnerabilities, including (1) prior risk for adverse pandemic outcomes due to population density and age and (2) the systems in place prior to the pandemic that may impact the ability to respond to the crisis, including health infrastructure and economic capacity. Our work demonstrates the importance of viewing vulnerability and resilience in a multi-dimensional way, where a country’s resources and outcomes related to vulnerability and resilience can differ dramatically across economic, political, and social domains. This work also highlights key gaps in our current understanding about vulnerability and resilience and a need for data-driven, context-specific assessments of disaster vulnerability in the future.

PMID:36603015 | DOI:10.1371/journal.pone.0279894

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Nevin Manimala Statistics

GCL loss in BRAO

PLoS One. 2023 Jan 5;18(1):e0279920. doi: 10.1371/journal.pone.0279920. eCollection 2023.

ABSTRACT

PURPOSE: Our recent publication used optical coherence tomography (OCT) to follow thinning of the retinal ganglion cell layer (GCL) in central retinal artery occlusion (CRAO). Thinning of the inner layers also occurs in patients with branch retinal artery occlusion (BRAO). The mechanism for such thinning may be partially due to proteolysis by a calcium-activated protease called calpain. Calpain inhibitor SNJ-1945 ameliorated the proteolysis in a past series of model experiments. The purposes of the present retrospective study were to: 1) use segmentation analysis of OCT images to follow the loss of retinal layers in BRAO compared to CRAO patients, and 2) predict the number of patients and days of observation needed for a clinical trial of a calpain inhibitor against BRAO.

METHODS: A retrospective, case control study was conducted by computer-aided search in a medical records database for BRAO (ICD10 Code H34.239) with at least one OCT procedure (CPT: 92134). Non-proliferative, co-morbid eye diseases were allowed in the patient data base, and manual correction of auto-segmentation errors was performed. GCL thickness changes were followed over time and Cohen-d/sample size statistics were used to predict minimal patients needed for drug trials.

RESULTS: The thickness of the GCL layer in BRAO decreased rapidly with time as in CRAO, but in more limited quadrants. The data, as fit to a single-phase decay curve, showed that GCL thickness could be used to provide sample size statistics in a clinical trial to test a calpain inhibitor. For example, a 60-day trial with a 60% effective inhibitor would need a minimum of 29 patients.

CONCLUSIONS: Using thickness changes in the GCL layer to monitor the efficacy of potential inhibitors against BRAO and CRAO is practical in human trials requiring a reasonable number of patients and relatively short trial period.

TRANSLATIONAL RELEVANCE: Measurement of GCL thickness would be a useful indicator of amelioration of BRAO and CRAO progression in a clinical trial of a putative inhibitor.

PMID:36603006 | DOI:10.1371/journal.pone.0279920

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Nevin Manimala Statistics

Women infertility and common mental disorders: A cross-sectional study from North India

PLoS One. 2023 Jan 5;18(1):e0280054. doi: 10.1371/journal.pone.0280054. eCollection 2023.

ABSTRACT

BACKGROUND: Infertility is a very distressing condition. It is often associated with long-term stress, which can emerge as anxiety and depression.

AIM: To understand the effect of socio-demographic variables, reproductive trajectories, and lifestyle variables on stress, depression, and anxiety independently and to understand the relationship of psychological variables with each other among infertile and fertile women.

METHODS: This cross-sectional study recruited 500 women which included 250 primary infertile cases and 250 age-matched fertile controls of the age group 22-35 years. A pretested modified interview schedule was administered which included demographic variables, lifestyle variables, and reproductive trajectories. In addition, psychological tools like PSS, GAD-7, and PHQ-9 were used to collect the data pertaining to Stress, anxiety, and depression, respectively. Data analysis was performed with the statistical software version SPSS, IBM version 24.

RESULTS: Infertile women are more prone to various psychological disorder (stress, anxiety and depression). None of the demographic and lifestyle variables were associated with stress, anxiety, and depression among infertile women. Only reproductive trajectories were found to be causing stress, anxiety, and depression respectively among infertile women. In addition, stress is leading to both anxiety and depression among infertile women but only to depression in fertile women.

CONCLUSION: Infertile women should be counselled by medical experts regarding reproductive trajectories. Infertile couples should be guided and counselled to incorporate mental health screening and treatment in their routine check-up.

PMID:36603005 | DOI:10.1371/journal.pone.0280054

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Nevin Manimala Statistics

Association between abdominal obesity and diabetic retinopathy in patients with diabetes mellitus: A systematic review and meta-analysis

PLoS One. 2023 Jan 5;18(1):e0279734. doi: 10.1371/journal.pone.0279734. eCollection 2023.

ABSTRACT

OBJECTIVE: Previous studies have reported different opinions regarding the association between abdominal obesity and diabetic retinopathy (DR) in patients with diabetes mellitus (DM). In this study, we aimed to investigate this problem through a systematic review and meta-analysis to provide a basis for clinical interventions.

METHODS: A comprehensive search was conducted in the PubMed, Embase, and Web of Science databases up to May 1, 2022, for all eligible observational studies. Standardized mean differences (SMD) and 95% confidence intervals (CI) were evaluated using a random-effects model in the Stata software. We then conducted, publication bias assessment, heterogeneity, subgroup and sensitivity analyses.

RESULTS: A total of 5596 DR patients and 17907 non-DR patients were included from 24 studies. The results of the meta-analysis of abdominal obesity parameters showed statistically significant differences between DR and non-DR patients in both type 1 and type 2 diabetes. Waist circumference (WC) was higher in patients with DR than in the non-DR patients. In the waist-hip ratio (WHR) subgroup, the level of WHR was higher in patients with DR than that in non-DR patients. The association between abdominal obesity and mild to moderate nonproliferative DR or vision-threatening DR groups did not show any statistical difference. Subgroup analysis according to ethnicity showed that Caucasians had higher levels of combined abdominal obesity parameters than Asians.

CONCLUSION: We found that abdominal obesity measured by WC and WHR is associated with DR in patients with type 1 and type 2 diabetes. This association is stronger in Caucasians than in Asians, where isolated abdominal obesity might be more related to DR. However, no correlation was found between abdominal obesity and varying degrees of diabetic retinopathy. Further prospective cohort studies with larger sample sizes are yet to be conducted to clarify our findings.

PMID:36603004 | DOI:10.1371/journal.pone.0279734