Distinguishing happiness and meaning in life from depressive symptoms: A GWAS-by-subtraction study in the UK Biobank

The association between metabolite concentrations and wellbeing in adults

The biological complexity of wellbeing is studied from various perspectives, including genetics and epigenetics. However, there is a knowledge gap concerning other layers, such as metabolomics, which is dynamic and changes throughout life. This study explores the association between metabolites and wellbeing in a sample (N = 4748) drawn from the Netherlands Twin Register. A latent factor score for wellbeing was constructed based on: Quality of Life, Life Satisfaction, and Subjective Happiness. A total of 231 blood metabolites were analyzed using 1HNMR technique. Linear regression models were performed for each metabolite, while correcting for family clustering, relevant covariates, and multiple testing. None of the metabolites were significantly associated with wellbeing after multiple testing correction. Despite the lack of significant findings, the 34 metabolites with the lowest p-value (0.25) pointed to the same metabolic pathway: endogenous lipid metabolism. This pathway has previously been linked to wellbeing in a GWAS and associated with related phenotypes in other metabolomic studies. In conclusion, this study confirms the biological complexity of wellbeing and speculates on a potential role of lipids. Further research is needed to confirm these hypotheses.

Meaning in life and all-cause and cause-specific mortality in the UK Biobank

OBJECTIVE

To determine the association between meaning in life and all-cause and cause-specific mortality, and whether associations vary by depression or sociodemographic factors.

METHODS

Participants were UK Biobank cohort members who reported on their meaning in life in the mental health assessment from October 2016 to July 2017 (N = 153,505). All-cause mortality and cause-specific mortality were identified from ICD-10 codes from national death registries through December 2022.

RESULTS

Over the up to six-year follow-up, every standard deviation higher in meaning in life was associated with a 15 % decreased risk of death from any cause (HR = 0.87, 95 % CI = 0.85-0.90, p < .001). The association was attenuated but remained significant accounting for socioeconomic, clinical, and behavioral risk factors (HR = 0.91, 95 % CI = 0.88-0.94, p < .001). Meaning in life was associated with reduced risk of death from 7 of the 8 cause-specific deaths examined: external cause (47 %), respiratory (41 %), nervous (32 %), digestive (25 %), or circulatory (15 %) systems, COVID-19 (28 %), and cancer (8 %). Depression concurrent with the meaning assessment did not explain or moderate these associations, which indicated that meaning was similarly protective when concurrently experiencing psychological distress. The association between meaning and all-cause mortality was similar across age, ethnicity, and socioeconomic status but slightly stronger among female than male participants.

CONCLUSION

Feeling that one's life has meaning is associated with lower risk of mortality, particularly causes of death due to the respiratory system, nervous system, or COVID-19. Given that meaning in life can be modified through intervention, future research could address whether it could be a useful target of intervention.

The stability and change of wellbeing across the lifespan: a longitudinal twin-sibling study

BACKGROUND

Wellbeing is relatively stable over the life span. However, individuals differ in this stability and change. One explanation for these differences could be the influence of different genetic or environmental factors on wellbeing over time.

METHODS

To investigate causes of stability and change of wellbeing across the lifespan, we used cohort-sequential data on wellbeing from twins and their siblings of the Netherlands Twin Register (NTR) (total N = 46.885, 56% females). We organized wellbeing data in multiple age groups, from childhood (age 5), to adolescence, up to old age (age 61+). Applying a longitudinal genetic simplex model, we investigated the phenotypic stability of wellbeing and continuity and change in genetic and environmental influences.

RESULTS

Wellbeing peaked in childhood, decreased during adolescence, and stabilized during adulthood. In childhood and adolescence, around 40% of the individual differences was explained by genetic effects. The heritability decreased toward old adulthood (35-24%) and the contribution of unique environmental effects increased to 76%. Environmental innovation was found at every age, whereas genetic innovation was only observed during adolescence (10-18 years). In childhood and adulthood, the absence of genetic innovation indicates a stable underlying set of genes influencing wellbeing during these life phases.

CONCLUSION

These findings provide insights into the stability and change of wellbeing and the genetic and environmental influences across the lifespan. Genetic effects were mostly stable, except in adolescence, whereas the environmental innovation at every age suggests that changing environmental factors are a source of changes in individual differences in wellbeing over time.

Assessment of the Genetic Characteristics of a Generation Born during a Long-Term Socioeconomic Crisis

BACKGROUND

A socioeconomic crisis in Russia lasted from 1991 to 1998 and was accompanied by a sharp drop in the birth rate. The main factor that influenced the refusal to have children during this period is thought to be prolonged social stress.

METHODS

comparing frequencies of common gene variants associated with stress-induced diseases among generations born before, after, and during this crisis may show which genes may be preferred under the pressure of natural selection during periods of increased social stress in urban populations.

RESULTS

In the "crisis" group, a statistically significant difference from the other two groups was found in rs6557168 frequency (p = 0.001); rs4522666 was not in the Hardy-Weinberg equilibrium in this group, although its frequency did not show a significant difference from the other groups (p = 0.118). Frequencies of VNTRs in SLC6A3 and MAOA as well as common variants rs17689918 in CRHR1, rs1360780 in FKBP5, rs53576 in OXTR, rs12720071 and rs806377 in CNR1, rs4311 in ACE, rs1800497 in ANKK1, and rs7412 and rs429358 in APOE did not differ among the groups.

CONCLUSIONS

a generation born during a period of prolonged destructive events may differ from the rest of the gene pool of the population in some variants associated with personality traits or stress-related disorders.