Demoralization isa common psychological problem in cancer patients. The purpose of this study is to systematically evaluate the correlated factors of demoralization among cancer patients. We also summarized the available evidence, effect estimates, and the strength of statistical associations between demoralization and its associated factors.

We systematically searched PubMed, Web of Science, CINAHL, Embase, the Cochrane Library, PsycINFO, and 2 electronic databases to identify studies published up to October 2023 with data on the correlates of demoralization. Two researchers independently reviewed references, extracted data, and assessed data quality. Meta-analysis was performed using R4.1.1 software.

Thirty-eight studies were included in this meta-analysis. For the most studied sociodemographic correlates, demoralization was negatively correlated with income (z = −0.29, 95% CI: −0.51, −0.02), education (z = − 0.11, 95% CI: − 0.16, −0.05), and age (z = −0.45, 95%CI: −0.75, −0.01). For the most studied clinical correlates, demoralization was positively correlated with symptom burden (z = 0.37, 95% CI: 0.22, 0.50) and negatively correlated with quality of life (z = −0.40, 95% CI: −0.54, −0.24). For the most studied psychosocial correlates, demoralization was negatively correlated with social support (z = −0.39, 95% CI: −0.51, −0.26) and positively correlated with anxiety (z = 0.65, 95% CI: 0.56, 0.73), depression (z = 0.61, 95% CI: 0.54, 0.67), and suicidal ideation (z = 0.48, 95% CI: 0.34, 0.60).

Demoralization showed either positive or negative associations with sociodemographic, clinical, and psychological variables. More research is needed to explore the underlying mechanisms to develop effective interventions. This review provides information on the factors associated with demoralization in cancer patients, which can be used to inform strategies for clinical care providers.

Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD.

This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5–10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model.

During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09–1.23), NO2 (HR: 1.12, 95% CI: 1.05–1.19), and NO (HR: 1.10, 95% CI: 1.03–1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46–1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5.

Our findings highlight the importance of air pollution control in alleviating the burden of MD.

Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).

The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.

Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10−8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10−8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10−3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10−3, preplication GWAS2 = 8.08 × 10−3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).

Our findings provide novel clues for understanding of the complex genetic architecture of depression.

The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ.

By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ.

LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = −0.165, p value = 0.035) and SCZ (coefficient = −0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10−6) and SCZ (OR = 0.90, p value = 4.04 × 10−6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level.

This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.

Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.

We observed 51 common diet–gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10−4, Pdepression status = 5.86 × 10−4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet–gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10−3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10−4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).

Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits–gut microbiome interactions with depression and anxiety.

Cognitive impairment is common in late-life depression, which may increase Alzheimer disease (AD) risk. Therefore, we aimed to investigate whether late-life major depressive disorder (MDD) has worse cognition and increases the characteristic AD neuropathology. Furthermore, we carried out a comparison between treatment-resistant depression (TRD) and non-TRD. We hypothesized that patients with late-life depression and TRD may have increased β-amyloid (Aβ) deposits in brain regions responsible for global cognition.

We recruited 81 subjects, including 54 MDD patients (27 TRD and 27 non-TRD) and 27 matched healthy controls (HCs). Neurocognitive tasks were examined, including Mini-Mental State Examination and Montreal Cognitive Assessment to detect global cognitive functions. PET with Pittsburgh compound-B and fluorodeoxyglucose were used to capture brain Aβ pathology and glucose use, respectively, in some patients.

MDD patients performed worse in Montreal Cognitive Assessment (p = 0.003) and had more Aβ deposits than HCs across the brain (family-wise error-corrected p < 0.001), with the most significant finding in the left middle frontal gyrus. Significant negative correlations between global cognition and prefrontal Aβ deposits existed in MDD patients, whereas positive correlations were noted in HCs. TRD patients had significantly more deposits in the left-sided brain regions (corrected p < 0.001). The findings were not explained by APOE genotypes. No between-group fluorodeoxyglucose difference was detected.

Late-life depression, particularly TRD, had increased brain Aβ deposits and showed vulnerability to Aβ deposits. A detrimental role of Aβ deposits in global cognition in patients with late-onset or non-late-onset MDD supported the theory that late-life MDD could be a risk factor for AD.

The aim of this study was to investigate risk factors and psychological stress of health-care workers (HCWs) with coronavirus disease 2019 (COVID-19) in a nonfrontline clinical department.

Data of 2 source patients and all HCWs with infection risk were obtained in a department in Wuhan from January to February 2020. A questionnaire was designed to evaluate psychological stress of COVID-19 on HCWs.

The overall infection rate was 4.8% in HCWs. Ten of 25 HCWs who contacted with 2 source patients were diagnosed with confirmed COVID-19 (8/10) and suspected COVID-19 (2/10). Other 2 HCWs were transmitted by other patients or colleagues. Close care behaviors included physical examination (6/12), life nursing (4/12), ward rounds (4/12), endoscopic examination (2/12). Contacts fluctuated from 1 to 24 times and each contact was short (8.1 min ± 5.6 min). HCWs wore surgical masks (11/12), gloves (7/12), and isolation clothing (3/12) when providing medical care. Most HCWs experienced a mild course with 2 asymptomatic infections, taking 9.8 d and 20.9 d to obtain viral shedding and clinical cure, respectively. Psychological stress included worry (58.3%), anxiety (83.3%), depression (58.3%), and insomnia (58.3%).

Close contact with COVID-19 patients and insufficient protection were key risk factors. Precaution measures and psychological support on COVID-19 is urgently required for HCWs.

Birth weight influences not only brain development, but also mental health outcomes, including depression, but the underlying mechanism is unclear.

The phenotypic data of 12,872–91,009 participants (59.18–63.38% women) from UK Biobank were included to test the associations between the birth weight, depression, and brain volumes through the linear and logistic regression models. As birth weight is highly heritable, the polygenic risk scores (PRSs) of birth weight were calculated from the UK Biobank cohort (154,539 participants, 56.90% women) to estimate the effect of birth weight-related genetic variation on the development of depression and brain volumes. Finally, the mediation analyses of step approach and mediation analysis were used to estimate the role of brain volumes in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations.

We observed associations between birth weight and depression (odds ratio [OR] = 0.968, 95% confidence interval [CI] = 0.957–0.979, p = 2.29 × 10−6). Positive associations were observed between birth weight and brain volumes, such as gray matter (B = 0.131, p = 3.51 × 10−74) and white matter (B = 0.129, p = 1.67 × 10−74). Depression was also associated with brain volume, such as left thalamus (OR = 0.891, 95% CI = 0.850–0.933, p = 4.46 × 10−5) and right thalamus (OR = 0.884, 95% CI = 0.841–0.928, p = 2.67 × 10−5). Additionally, significant mediation effects of brain volume were found for the associations between birth weight and depression through steps approach and mediation analysis, such as gray matter (B = –0.220, p = 0.020) and right thalamus (B = –0.207, p = 0.014).

Our results showed the associations among birth weight, depression, and brain volumes, and the mediation effect of brain volumes also provide evidence for the sex-specific of associations.

Dietary salt intake may vary depending on different lifestyles. We aimed to estimate the different salt intakes and evaluate the knowledge and self-awareness about salt among people speaking the Teochew, Teochew–Hakka and Hakka dialects in the Chaoshan region of southern China.

The study followed a cluster sampling of residents in Chaoshan region. General characteristics, lifestyles, health status as well as knowledge and self-awareness related to salt intake were investigated using a questionnaire. Anthropometric variables as well as Na and K excretion in a 24-h urine collection were measured.

Chaoshan region of China.

Four hundred fifteen adults who spoke only one of these three dialects.

The salt intake of adults who spoke the Teochew, Teochew–Hakka and Hakka dialects was 7·19 (interquartile range (IQR) 5·29–10·17), 9·03 (IQR 6·62–11·54) and 10·12 (IQR 7·61–12·82) g/d, respectively, with significant differences between Teochew and Teochew–Hakka speakers and between Teochew and Hakka speakers (both P < 0·05). The Na:K ratio for adults who spoke the three dialects was 3·00 (IQR 2·00–4·11), 3·50 (IQR 2·64–4·82) and 4·52 (IQR 3·35–5·97), respectively, and differed significantly among the groups (all P < 0·05). Multiple linear regression analysis showed increased Na:K ratio associated with hypertension (β = 0·71, P = 0·043) in Hakka speakers. Knowledge and self-awareness about salt intake were poor in this population.

Salt intake was closely related to lifestyles and was higher than the upper limit (5 g/d) recommended by the WHO in adults of Chaoshan, especially those speaking the Hakka dialect.

The microbiota–gut–brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients.

We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD.

The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890.

The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.

Major depressive disorder (MDD) is highly heterogeneous and can be classified as treatment-resistant depression (TRD) or antidepressant-responsive depression (non-TRD) based on patients' responses to antidepressant treatment. Methods for distinguishing between TRD and non-TRD are critical clinical concerns. Deficits of cortical inhibition (CI) have been reported to play an influential role in the pathophysiology of MDD. Whether TRD patients' CI is more impaired than that of non-TRD patients remains unclear.

Paired-pulse transcranial magnetic stimulation (ppTMS) was used to measure cortical inhibitory function including GABAA- and GABAB-receptor-related CI and cortical excitatory function including glutamate-receptor-related intracortical facilitation (ICF). We recruited 36 healthy controls (HC) and 36 patients with MDD (non-TRD, n = 16; TRD, n = 20). All participants received evaluations for depression severity and ppTMS examinations. Non-TRD patients received an additional ppTMS examination after 3 months of treatment with the SSRI escitalopram.

Patients with TRD exhibited reduced short-interval intracortical inhibition (SICI) and long-interval intracortical inhibition (LICI), as shown by abnormally higher estimates, than those with non-TRD or HC (F = 11.030, p < 0.001; F = 10.309, p < 0.001, respectively). After an adequate trial of escitalopram treatment, the LICI of non-TRD reduced significantly (t = − 3.628, p < 0.001), whereas the ICF remained lower than that of HC and showed no difference from pretreatment non-TRD.

TRD was characterized by relatively reduced CI, including both GABAA- and GABAB-receptor-mediated neurons while non-TRD preserved partial CI. In non-TRD, SSRIs may mainly modulate GABAB-receptor-related LICI. Our findings revealed distinguishable features of CI in antidepressant-resistant and responsive major depression.