The role of genetic variation of human metabolism for BMI, mental traits and mental disorders

A narrative review about cognitive impairment in metabolic Dysfunction-Associated liver disease (MASLD): Another matter to face through a holistic approach

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic hepatic disorder worldwide in both adults and children. It is well established that MASLD represents the hepatic manifestation of the metabolic syndrome whose definition includes the presence of obesity, type 2 diabetes (T2D), dyslipidemia, hypertension and hypercoagulability. All these conditions contribute to a chronic inflammatory status which may impact on blood brain barrier (BBB) integrity leading to an impaired function of central nervous system (CNS).

AIM OF REVIEW

Since the mechanisms underlying the brain-liver-gut axis derangement are still inconclusive, the present narrative review aims to make a roundup of the most recent studies regarding the cognitive decline in MASLD also highlighting possible therapeutic strategies to reach a holistic advantage for the patients.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Due to its ever-growing prevalence, the MASLD-related mental dysfunction represents an enormous socio-economic burden since it largely impacts on the quality of life of patients as well as on their working productivity. Indeed, cognitive decline in MASLD translates in low concentration and processing speed, reduced memory, sleepiness but also anxiety and depression. Chronic systemic inflammation, hyperammonemia, genetic background and intestinal dysbiosis possibly contribute to the cognitive decline in MASLD patients. However, its diagnosis is still underestimated since the leading mechanisms are multi-faceted and unexplained and do not exist standardized diagnostic tools or cognitive test strategies. In this scenario, nutritional and lifestyle interventions as well as intestinal microbiota manipulation (probiotics, fecal transplantation) may represent new approaches to counteract mental impairment in these subjects. In sum, to face the "mental aspect" of this multifactorial disease which is almost unexplored, cognitive tools should be introduced in the management of MASLD patients.

Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids

BACKGROUND

Metabolic differences have been reported between individuals with and without major depressive disorder (MDD), but their consistency and causal relevance have been unclear.

METHODS

We conducted a metabolome-wide association study of MDD with 249 metabolomic measures available in the UK Biobank (n = 29,757). We then applied two-sample bidirectional Mendelian randomization and colocalization analysis to identify potentially causal relationships between each metabolite and MDD.

RESULTS

A total of 191 metabolites tested were significantly associated with MDD (false discovery rate-corrected p < .05), which decreased to 129 after adjustment for likely confounders. Lower abundance of omega-3 fatty acid measures and a higher omega-6 to omega-3 ratio showed potentially causal effects on liability to MDD. There was no evidence of a causal effect of MDD on metabolite levels. Furthermore, genetic signals associated with docosahexaenoic acid colocalized with loci associated with MDD within the fatty acid desaturase gene cluster. Post hoc Mendelian randomization of gene-transcript abundance within the fatty acid desaturase cluster demonstrated a potentially causal association with MDD. In contrast, colocalization analysis did not suggest a single causal variant for both transcript abundance and MDD liability, but rather the likely existence of two variants in linkage disequilibrium with one another.

CONCLUSIONS

Our findings suggest that decreased docosahexaenoic acid and increased omega-6 to omega-3 fatty acids ratio may be causally related to MDD. These findings provide further support for the causal involvement of fatty acids in MDD.

Alterations of Urinary Microbial Metabolites and Immune Indexes Linked With COVID-19 Infection and Prognosis

Coronavirus disease 2019 (COVID-19) has evolved into an established global pandemic. Metabolomic studies in COVID-19 patients is worth exploring for further available screening methods. In our study, we recruited a study cohort of 350 subjects comprising 248 COVID-19 patients (161 non-severe cases, 60 asymptomatic cases, and 27 severe cases) and 102 healthy controls (HCs), and herein present data with respect to their demographic features, urinary metabolome, immunological indices, and follow-up health status. We found that COVID-19 resulted in alterations of 39 urinary, mainly microbial, metabolites. Using random forest analysis, a simplified marker panel including three microbial metabolites (oxoglutaric acid, indoxyl, and phenylacetamide) was constructed (AUC=0.963, 95% CI, 0.930-0.983), which exhibited higher diagnostic performance than immune feature-based panels between COVID-19 and HC groups (P<0.0001). Meanwhile, we observed that urine metabolic markers enabled discriminating asymptomatic patients (ASY) from HCs (AUC = 0.981, 95% CI, 0.946-0.996), and predicting the incidence of high-risk sequalae in COVID-19 individuals (AUC=0.931, 95% CI, 0.877-0.966). Co-expression network analysis showed that 13 urinary microbial metabolites (e.g., oxoglutaric acid) were significantly correlated with alterations of CD4⁺, CD3⁺, and CD8⁺ T-cells, as well as IFN-γ, IL-2 and IL-4 levels, suggesting close interactions between microbial metabolites and host immune dysregulation in COVID-19. Taken together, our findings indicate that urinary metabolites may have promising potential for screening of COVID-19 in different application scenarios, and provide a new entry point to understand the microbial metabolites and related immune dysfunction in COVID-19.

A mendelian randomization study on causal effects of 25(OH)vitamin D levels on attention deficit/hyperactivity disorder

BACKGROUND

While observational studies revealed an inverse association between serum 25(OH)vitamin D (25(OH)D) and the risk of attention deficit/hyperactivity disorder (ADHD), the causality of this relationship remains unclear.

METHODS

We conducted a bidirectional two-sample Mendelian Randomization (MR) study to examine whether 25(OH)D has an effect on the risk to develop ADHD or vice versa. Information on single nucleotide polymorphisms (SNP) associated with serum 25(OH)D was obtained from a genome-wide association study (GWAS) considering phenotype data from 79,366 individuals of European ancestry. Data on risk for ADHD were derived from a GWAS analysis with 20,183 individuals diagnosed with ADHD and 35,191 controls. For our analysis, we considered effect sizes based on the European participants (19,099 cases and 34,194 controls).

RESULTS

Single SNP analyses showed a causal effect of vitamin D on ADHD risk for only one SNP (rs12785878, p = 0.024). The overall MR estimates did not reveal a causal effect of 25(OH)D on risk for ADHD. In the reverse analysis, neither any single nor the multi-SNP MR analyses showed a causal effect of ADHD on 25(OH)D.

CONCLUSION

Results from this two-sample MR study did not confirm a causal effect of 25(OH)D on ADHD or vice versa. Accordingly, our study does not provide evidence that improving 25(OH)D via supplementation could reduce the risk of developing ADHD.

[Nutrition and mental health - how findings from genetic studies can support the identification of dietary effects]

Nutrition and mental health - how findings from genetic studies can support the identification of dietary effects Abstract. Introduction: Numerous studies indicate that dietary interventions could be an important approach to the prevention and treatment of mental disorders. However, conventional nutritional epidemiological approaches (e. g., observational studies and randomized controlled trials, RCTs) have specific limitations to consider when interpreting the results. This article examines whether genetic studies could help to establish a link between diet and the prevention of mental disorders. Furthermore, it examines whether it is possible to draw conclusions about causal relationships. Methods: This narrative review describes various approaches of genetic cross-phenotype studies and presents examples of their applications in nutritional psychiatry. In addition, it discusses specific requirements as well as the strengths and limitations of the respective approaches. Results: To date, in the context of nutritional psychiatry, genetic correlation analyses, look-up analyses, and Mendelian randomization (MR) studies have been used for genetic crossphenotype analyses. Genetic correlation and look-up analyses provide initial evidence of possible overlap between specific mental disorders and metabolic pathways or specific nutrients. MR studies are used for detailed analyses that aim to identify causal relationships. However, MR is based on specific assumptions that must be met and considered when results are interpreted. Conclusion: Genetic cross-phenotype analyses are a useful amendment to conventional nutritional epidemiological research. In particular, positive results from MR studies provide an important fundament for identifying and developing suitable dietary interventions, which in turn increases the chance of success upon testing in subsequent RCTs. Accordingly, genetic cross-phenotype analyses are important instruments for increasing the efficiency in nutritional psychiatric research.

Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction

Extracellular matrix (ECM) remodeling plays important roles in both white adipose tissue (WAT) and the skeletal muscle (SM) metabolism. Excessive adipocyte hypertrophy causes fibrosis, inflammation, and metabolic dysfunction in adipose tissue, as well as impaired adipogenesis. Similarly, disturbed ECM remodeling in SM has metabolic consequences such as decreased insulin sensitivity. Most of described ECM molecular alterations have been associated with DNA sequence variation, alterations in gene expression patterns, and epigenetic modifications. Among others, the most important epigenetic mechanism by which cells are able to modulate their gene expression is DNA methylation. Epigenome-Wide Association Studies (EWAS) have become a powerful approach to identify DNA methylation variation associated with biological traits in humans. Likewise, Genome-Wide Association Studies (GWAS) and gene expression microarrays have allowed the study of whole-genome genetics and transcriptomics patterns in obesity and metabolic diseases. The aim of this review is to explore the molecular basis of ECM in WAT and SM remodeling in obesity and the consequences of metabolic complications. For that purpose, we reviewed scientific literature including all omics approaches reporting genetic, epigenetic, and transcriptomic (GWAS, EWAS, and RNA-seq or cDNA arrays) ECM-related alterations in WAT and SM as associated with metabolic dysfunction and obesity.

Cross-sectional metabolic profiles of mental health in population-based cohorts of 11- to 12-year-olds and mid-life adults: The Longitudinal Study of Australian Children

OBJECTIVE

Poorer mental health in adulthood is associated with increased risk of cardiovascular disease and reduced life expectancy. However, little is known of the molecular pathways underpinning this relationship and how early in life adverse metabolite profiles relate to self-reported variation in mental health. We examined cross-sectional associations between mental health and serum metabolites indicative of cardiovascular health, in large Australian population-based cohorts at two stages of the life-course.

METHODS

We characterised cross-sectional serum nuclear magnetic resonance metabolite profiles of positively and negatively framed mental health in a large population-based sample of Australian 11- to 12-year-olds (n = 1172; 51% girls) and mid-life adults (n = 1322; mean age 45 years; 87% women). We examined multiple standard self-report mental health scales, spanning psychosocial health, general well-being, life satisfaction, and health-related quality of life. Linear regression was used to investigate the cross-sectional association between mental health and each metabolite (n = 73) in children and adults separately, unadjusted and adjusted for age, sex, socioeconomic position and body mass index.

RESULTS

Better child and adult mental health were associated with lower levels of the inflammatory marker glycoprotein acetyls, and a favourable, less atherogenic lipid/lipoprotein profile. Patterns of association in children were generally weaker than in adults. Associations were generally modest and partially attenuated when adjusted for body mass index.

CONCLUSIONS

In general, metabolite profiles associated with better child and adult mental health closely aligned with those predictive of better cardiovascular health in adults. Our findings support previous evidence for the likely bidirectional relationship between mental health and cardiovascular disease risk, by extending this evidence base to the molecular level and in children.

Genetic and epigenetic findings in anorexia nervosa

Polygenic factors are relevant for the genetic predispositions to the eating disorder anorexia nervosa (AN). The most recent genome-wide association study (GWAS) for AN comprised almost 17,000 patients with AN and controls. A total of eight genome-wide significant polygenic loci associated with AN have been identified. Each single polygenic locus makes only a small contribution to the development of AN. Analyses across different traits successfully identified regions/genes for AN that had not been detected by analyses of the single traits. Functional studies of the genes derived by GWAS studies aim to improve the understanding of the biological mechanisms involved in eating disorders. Epigenetic studies have not yet successfully contributed to the understanding of AN.

The Role of Genetic Variation of BMI, Body Composition, and Fat Distribution for Mental Traits and Disorders: A Look-Up and Mendelian Randomization Study

Anthropometric traits and mental disorders or traits are known to be associated clinically and to show genetic overlap. We aimed to identify genetic variants with relevance for mental disorders/traits and either (i) body mass index (or obesity), (ii) body composition, (and/or) (iii) body fat distribution. We performed a look-up analysis of 1,005 genome-wide significant SNPs for BMI, body composition, and body fat distribution in 15 mental disorders/traits. We identified 40 independent loci with one or more SNPs fulfilling our threshold significance criterion (P < 4.98 × 10-5) for the mental phenotypes. The majority of loci was associated with schizophrenia, educational attainment, and/or intelligence. Fewer associations were found for bipolar disorder, neuroticism, attention deficit/hyperactivity disorder, major depressive disorder, depressive symptoms, and well-being. Unique associations with measures of body fat distribution adjusted for BMI were identified at five loci only. To investigate the potential causality between body fat distribution and schizophrenia, we performed two-sample Mendelian randomization analyses. We found no causal effect of body fat distribution on schizophrenia and vice versa. In conclusion, we identified 40 loci which may contribute to genetic overlaps between mental disorders/traits and BMI and/or shape related phenotypes. The majority of loci identified for body composition overlapped with BMI loci, thus suggesting pleiotropic effects.

Assessing causal links between metabolic traits, inflammation and schizophrenia: a univariable and multivariable, bidirectional Mendelian-randomization study

BACKGROUND

Blood immunoreactive biomarkers, such as C-reactive protein (CRP), and metabolic abnormalities have been associated with schizophrenia. Studies comprehensively and bidirectionally probing possible causal links between such blood constituents and liability to schizophrenia are lacking.

METHODS

To disentangle putative causal links between CRP blood levels and schizophrenia in both directions, we conducted multiple univariable Mendelian-randomization (MR) analyses, ranging from fixed-effect to inverse variance-weighted (IVW), weighted-median, MR Egger and generalized summary-data-based Mendelian-randomization (GSMR) models. To prioritize metabolic risk factors for schizophrenia, a novel multivariable approach was applied: multivariable Mendelian-randomization-Bayesian model averaging (MR-BMA).

RESULTS

All forward univariable MR analyses consistently showed that CRP has a protective effect on schizophrenia, whereas reverse MR analyses consistently suggested absent causal effects of schizophrenia liability on CRP blood levels. Using MR-BMA, as the top protective factors for schizophrenia we prioritized leucine and as the prime risk-factor triglycerides in medium very-low-density lipoprotein (VLDL). The five best-performing MR-BMA models provided one additional risk factor: triglycerides in large VLDL; and two additional protective factors: citrate and lactate.

CONCLUSIONS

Our results add to a growing body of literature hinting at metabolic changes-in particular of triglycerides-independently of medication status in schizophrenia. We also highlight the absent effects of genetic liability to schizophrenia on CRP levels.

Associations of Different Types of Maternal Diabetes and Body Mass Index With Offspring Psychiatric Disorders

IMPORTANCE

Maternal obesity, pregestational type 1 and 2 diabetes, and gestational diabetes have been reported to increase the risk of autism spectrum disorder and attention-deficit/hyperactivity disorder in the mothers' offspring. However, the associations of maternal diabetes disorders and body mass index jointly with psychiatric disorders among offspring are less well documented, especially for type 2 diabetes.

OBJECTIVE

To examine the associations of different types of maternal diabetes, separately and together with maternal obesity, with psychiatric disorders in the mothers' offspring.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study used data from nationwide registries in Finland encompassing all 649 043 live births occurring between 2004 and 2014. The study and data analysis were conducted from January 1, 2019, to July 5, 2019.

EXPOSURES

Maternal prepregnancy body mass index, insulin-treated pregestational diabetes, and pregestational type 2 diabetes and gestational diabetes without insulin treatment.

MAIN OUTCOMES AND MEASURES

Psychiatric diagnoses and prescription of psychotropic drugs among the mothers' offspring. Cox proportional hazards models were adjusted for birth year, sex, mode of delivery, maternal age, number of fetuses, parity, mother's country of birth, mother's marital status, maternal smoking, maternal psychiatric disorder, and maternal systemic inflammatory disease.

RESULTS

The mean (SD) age of mothers was 30.20 (5.37) years; 357 238 of 394 302 mothers (90.6%) were born in Finland. Of the 647 099 births studied, 4000 fetuses (0.62%) were exposed to maternal insulin-treated pregestational diabetes, 3724 (0.57%) were exposed to type 2 diabetes, and 98 242 (15.18%) were exposed to gestational diabetes; 34 892 offspring (5.39%) later received a diagnosis of a mild neurodevelopmental or psychiatric disorder. Non-insulin-treated type 2 diabetes in severely obese mothers, compared with normal-weight mothers without diabetes, was associated with psychiatric disorders in the offspring (hazard ratio, 1.97; 95% CI, 1.64-2.37), although with a lower effect size than that for severely obese mothers with insulin-treated pregestational diabetes (hazard ratio, 2.71; 95% CI, 2.03-3.61). The largest effect sizes were found for mood disorders, attention-deficit/hyperactivity disorder and conduct disorders, and autism. Gestational diabetes in severely obese mothers had a lower overall effect size (hazard ratio, 1.61; 95% CI, 1.50-1.72). Diabetes in normal-weight mothers was not associated with psychopathologic disorders in the offspring.

CONCLUSIONS AND RELEVANCE

Severe obesity in mothers with diabetes was associated with an increased overall risk for psychiatric disorders in their offspring. The risk was highest for those exposed to insulin-treated pregestational diabetes, followed by non-insulin-treated type 2 diabetes and gestational diabetes. These findings may have implications for managing pregnancies.

Nutritional psychiatry: Towards improving mental health by what you eat

Does it matter what we eat for our mental health? Accumulating data suggests that this may indeed be the case and that diet and nutrition are not only critical for human physiology and body composition, but also have significant effects on mood and mental wellbeing. While the determining factors of mental health are complex, increasing evidence indicates a strong association between a poor diet and the exacerbation of mood disorders, including anxiety and depression, as well as other neuropsychiatric conditions. There are common beliefs about the health effects of certain foods that are not supported by solid evidence and the scientific evidence demonstrating the unequivocal link between nutrition and mental health is only beginning to emerge. Current epidemiological data on nutrition and mental health do not provide information about causality or underlying mechanisms. Future studies should focus on elucidating mechanism. Randomized controlled trials should be of high quality, adequately powered and geared towards the advancement of knowledge from population-based observations towards personalized nutrition. Here, we provide an overview of the emerging field of nutritional psychiatry, exploring the scientific evidence exemplifying the importance of a well-balanced diet for mental health. We conclude that an experimental medicine approach and a mechanistic understanding is required to provide solid evidence on which future policies on diet and nutrition for mental health can be based.

Methamphetamine (MA) Use Induces Specific Changes in LINE-1 Partial Methylation Patterns, Which Are Associated with MA-Induced Paranoia: a Multivariate and Neuronal Network Study

The use of psychoactive substances, including methamphetamine (MA) may cause changes in DNA methylation. The aim of this study was to examine the effects of MA use on long interspersed element-1 (LINE-1) methylation patterns in association with MA-induced paranoia. This study recruited 123 normal controls and 974 MA users, 302 with and 672 without MA-induced paranoia. The Semi-Structured Assessment for Drug Dependence and Alcoholism was used to assess demographic and substance use variables. Patterns of LINE-1 methylation were assessed in peripheral blood mononuclear cells and a combined bisulfite restriction analysis (COBRA) was used to estimate overall LINE-1 methylation (mC) while COBRA classified LINE-alleles into four patterns based on the methylation status of two CpG dinucleotides on each strand from 5' to 3', namely two methylated (mCmC) and two unmethylated (uCuC) CpGs and two types of partially methylated loci (mCuC that is 5'm with 3'u and uCmC that is 5'u with 3'm CpGs). MA users showed higher % mCuC and % mCuC + uCmC levels than controls. Use of solvents and opioids, but not cannabis and alcohol dependence, significantly lowered % uCmC levels, while current smoking significantly increased % uCuC levels. MA-induced paranoia was strongly associated with changes in LINE-1 partial methylation patterns (lowered % uCmC), heavy MA use, lower age at onset of MA use, and alcohol dependence. Women who took contraceptives showed significantly lower LINE-1 % mC and % mCmC and higher % uCuC levels than women without contraceptive use and men. The results show that MA-induced changes in LINE-1 partial methylation patterns are associated with MA-induced paranoia and could explain in part the pathophysiology of this type of psychosis. It is argued that MA-induced neuro-oxidative pathways may have altered LINE-1 partial methylation patterns, which in turn may regulate neuro-oxidative and immune pathways, which may increase risk to develop MA-induced paranoia.