Genetic underpinnings of affective temperaments: a pilot GWAS investigation identifies a new genome-wide significant SNP for anxious temperament in ADGRB3 gene

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Affective temperaments show stronger association with infertility treatment success compared to somatic factors, highlighting the role of personality focused interventions

Infertility has a multifactorial background, where, besides somatic factors, psychological contributors also play a role in development and outcome. While affective temperaments have been associated with development, course, and outcome as well as treatment success in various somatic conditions, their association with infertility and its treatment has not been investigated so far. The purpose of our retrospective cohort study was to evaluate the influence of affective temperaments on fertility treatment outcomes. Among 578 women who underwent infertility treatment in an Assisted Reproduction Centre in Budapest, Hungary, treatment success, detailed medical history, and demographic parameters were recorded, and the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Auto-questionnaire (TEMPS-A) was administered. Possible predictors of assisted reproduction outcome were analyzed using multivariate logistic regression models, followed by a receiver operating curve (ROC) analysis in order to define ideal affective temperament cut-off values for clinical applicability. Aside from age, BMI, and previous miscarriage, cyclothymic scores > 4 (OR = 0.51 CI 0.35-0.74, p < 0.001), depressive scores > 9 (OR = 0.59 CI 0.4-0.87, p = 0.009) and anxious scores > 9 (OR = 0.45 CI 0.31-0.66, p < 0.001) significantly decreased the odds of clinical pregnancy by 49%, 41% and 55%, respectively. Irritable and hyperthymic temperaments, as well as other somatic and socio-economic factors had no effect on infertility treatment outcomes. The results suggest that affective temperaments may be related to the outcome of infertility treatments. Thus, screening for affective temperaments may help identify high-risk patient groups and offer patient-tailored treatment, which may increase the chances of a successful pregnancy and live birth for women undergoing IVF treatment.

Prognostic Role of Prolactin-Induced Protein (PIP) in Breast Cancer

Prolactin-inducible protein (PIP), also referred to as gross cystic disease fluid protein 15 (GCDFP-15), has been a trending topic in recent years due to its potential role as a specific marker in breast cancer. PIP binds to aquaporin-5 (AQP5), CD4, actin, fibrinogen, β-tubulin, serum albumin, hydroxyapatite, zinc α2-glycoprotein, and the Fc fragment of IgGs, and the expression of PIP has been demonstrated to be modulated by various cytokines, including IL4/13, IL1, and IL6. PIP gene expression has been extensively studied due to its captivating nature. It is influenced by various factors, with androgens, progesterone, glucocorticosteroids, prolactin, and growth hormone enhancing its expression while estrogens suppress it. The regulatory mechanisms involve important proteins such as STAT5A, STAT5B, Runx2, and androgen receptor, which collaborate to enhance PIP gene transcription and protein production. The expression level of PIP in breast cancer is dependent on the tumor stage and subtype. Higher expression is observed in early-stage tumors of the luminal A subtype, while lower expression is associated with luminal B, basal-like, and triple-negative subtypes, which have a poorer prognosis. PIP expression is also correlated with apocrine differentiation, hormone receptor positivity, and longer metastasis-free survival. PIP plays a role in supporting the immune system's antitumor response during the early stages of breast cancer development. However, as cancer progresses, the protective role of PIP may become less effective or diminished. In this work, we summarized the clinical significance of the PIP molecule in breast cancer and its potential role as a new candidate for cell-based therapies.

Genetic impact on the association of sleep patterns and chronic kidney disease: A prospective cohort study of 157,175 UK Biobank participants

OBJECTIVES

The association between sleep pattern and chronic kidney disease (CKD) incidence, and whether the association is dependent on the genetic backgrounds has not been addressed. We sought to investigate the association of multidimensional sleep pattern with CKD in consideration of genetic polymorphisms.

METHODS

In this prospective cohort study of 157,175 participants from the UK Biobank, sleep patterns were derived by multiple correspondence analysis (MCA) and k-means clustering of individual sleep traits (sleep duration, insomnia, chronotype, daytime sleepiness, snoring, and night shift status). Cox proportional hazard regression was used to estimate the association between sleep patterns and CKD incidence. Gene-environment-wide interaction study (GEWIS) was performed to detect whether gene polymorphisms were modifiers on this association.

RESULTS

Compared with "healthy sleep" pattern, increased CKD incidence was observed in the clusters with "long sleep duration" (hazard ratios (HR) 1.42, 95% confidence intervals (CI), 1.18-1.72) and "night shift" (HR 1.23, 95% CI, 1.05-1.45) patterns, but not with the "short sleep duration" pattern. By GEWIS, we identified 167 SNPs as suggestive effect modifiers that interacted with unhealthy sleep patterns and affected the risk of CKD.

CONCLUSIONS

Unhealthy sleep patterns, with features of long sleep duration and night shift, may increase the risk of CKD. The study highlights the interaction of sleep and individual genetic risk to affect health outcomes.

Research on Pathogenic Hippocampal Voxel Detection in Alzheimer's Disease Using Clustering Genetic Random Forest

Alzheimer's disease (AD) is an age-related neurological disease, which is closely associated with hippocampus, and subdividing the hippocampus into voxels can capture subtle signals that are easily missed by region of interest (ROI) methods. Therefore, studying interpretable associations between voxels can better understand the effect of voxel set on the hippocampus and AD. In this study, by analyzing the hippocampal voxel data, we propose a novel method based on clustering genetic random forest to identify the important voxels. Specifically, we divide the left and right hippocampus into voxels to constitute the initial feature set. Moreover, the random forest is constructed using the randomly selected samples and features. The genetic evolution is used to amplify the difference in decision trees and the clustering evolution is applied to generate offspring in genetic evolution. The important voxels are the features that reach the peak classification. The results demonstrate that our method has good classification and stability. Particularly, through biological analysis of the obtained voxel set, we find that they play an important role in AD by affecting the function of the hippocampus. These discoveries demonstrate the contribution of the voxel set to AD.

Relationships of affective temperament ratings to diagnosis and morbidity measures in major affective disorders

BACKGROUND

Ratings of affective temperament types show promise in helping to differentiate diagnostic groups among major affective disorders as well as to predict associations with important aspects of morbidity including suicidal risk.

METHODS

The Temperament Evaluation of Memphis, Pisa, Paris, and San Diego auto-rating (TEMPS-A) questionnaire was completed by 858 unselected, consecutive, consenting adults diagnosed with a DSM-5 major affective disorder (173 bipolar-1 [BD-1]), 250 BD-2, 435 major depressive disorder [MDD]) to score for anxious (anx), cyclothymic (cyc), dysthymic (dys), hyperthymic (hyp), and irritable (irr) affective temperaments. We tested their associations with diagnosis and selected clinical factors, including diagnosis, depression scores, suicidal ideation or acts, substance abuse, episodes/year, and %-time ill.

RESULTS

Scores for cyc ranked: BD-2 > BD-1 > MDD; anx ranked: MDD > BD-2 > BD-1; irr was greater in BD than MDD; dys was greater in MDD than BD; hyp did not differ by diagnosis. We confirmed associations of suicidal risk with higher scores of all temperament types except lower hyp scores. Higher cyc and irr scores and lower anx scores were associated with substance abuse. Several scores were higher with measures of greater affective morbidity: cyc with current depression, episodes/year, and %-time ill; irr with more episodes and depressions/year and greater %-time manic. Some of these associations were selective for BD or MDD.

CONCLUSIONS

The findings indicate that TEMPS-A ratings of affective temperament types can contribute to differential diagnoses and predict types and amounts of affective morbidity, as well as detecting suicidal risks.