Mark E. S. Bailey

Background: The link between cardiometabolic disease and mental illness has been well established but remains incompletely explained. One hypothesis suggests that circadian rhythm dysregulation links cardiometabolic disease and mental illnesses. BMAL1 is a circadian rhythm regulatory gene. Human genetic studies have implicated BMAL1 in depression, schizophrenia, bipolar disorder as well as body mass index, blood pressure and lipid levels. Objective: We investigated the BMAL1 locus genetic variants for associations with both cardiometabolic and mental illness. Methods: Genetic and phenotypic data from UK Biobank (~500 000 participants) of White British, African-Caribbean, South Asian, white European and Multiple ancestries were used. Regression analyses using Plink 1.09 was used to identify significant associations, with Bonferroni multiple testing correction. Multiple ancestry meta-analyses using METAL software was used to investigate trans-ancestry consistency in genetic effects. Findings: We identified associations for body mass index, anhedonia, diastolic and systolic blood pressure, waist-hip ratio, major depressive disorder, neuroticism and risk-taking. Meta-analyses indicated that there are ancestry-wide and ancestry-specific effects on cardiometabolic, mental illness and related traits. Conclusions: Our results suggest that the associations for mental illness (and related traits) and those for cardiometabolic traits are distinct rather than shared and that these associations were consistent across ancestry groups. Clinical implications: Further investigation into the tissue-specific roles of BMAL1 is required to fully understand the clinical impact of these findings.

UK Biobank is a prospective cohort study of around half-a-million general population participants, recruited between 2006 and 2010, with baseline studies at recruitment and multiple assessments since. From 2014 to date, magnetic resonance imaging (MRI) has been pursued in a participant sub-sample, with the aim to scan around n = 100k. This sub-sample is studied widely and therefore understanding its relative characteristics is important for future reports. We aimed to quantify psychological and physical health in the UK Biobank imaging sub-sample, compared with the rest of the cohort. We used t-tests and χ² for continuous/categorical variables, respectively, to estimate average differences on a range of cognitive, mental and physical health phenotypes. We contrasted baseline values of participants who attended imaging (versus had not), and compared their values at the imaging visit versus baseline values of participants who were not scanned. We also tested the hypothesis that the associations of established risk factors with worse cognition would be underestimated in the (hypothesized) healthier imaging group compared with the full cohort. We tested these interactions using linear regression models. On a range of cognitive, mental health, cardiometabolic, inflammatory and neurological phenotypes, we found that 47 920 participants who were scanned by January 2021 showed consistent statistically significant ‘healthy’ bias compared with the ∼450 000 who were not scanned. These effect sizes were small to moderate based on Cohen’s d/Cramer’s V metrics (range = 0.02 to −0.21 for Townsend, the largest effect size). We found evidence of interaction, where stratified analysis demonstrated that associations of established cognitive risk factors were smaller in the imaging sub-sample compared with the full cohort. Of the ∼100 000 participants who ultimately will undergo MRI assessment within UK Biobank, the first ∼50 000 showed some ‘healthy’ bias on a range of metrics at baseline. Those differences largely remained at the subsequent (first) imaging visit, and we provide evidence that testing associations in the imaging sub-sample alone could lead to potential underestimation of exposure/outcome estimates.

We present a genome-wide association study of a general happiness measure in 118,851 participants from the UK Biobank. Using BOLT-LMM, we identify 3 significant loci with a heritability estimate of 0.8%. Linkage disequilibrium score regression was performed on the ‘big five’ personality traits finding significant associations with lower neuroticism and higher extraversion and conscientiousness. Using a novel approach, we construct LDpred-inf polygenic risk scores in the Adolescent Brain Cognitive Development (ABCD) cohort and the Add Health cohort. We detected nominally significant associations with several well-being measures in ABCD and significant correlations with a happiness measure in Add Health. Additionally, we tested for associations with several brain regions in a white British subsample of UK Biobank finding significant associations with several brain structure and integrity phenotypes. We demonstrated a genetic basis for general happiness level and brain structure that appears to remain consistent throughout the lifespan and across multiple ancestral backgrounds. Author summary At the genetic level, there has been little investigation into whether people may have a baseline happiness level which varies from person to person. Here we perform a genetic analysis in the UK Biobank to identify three genetic loci that associate with general happiness level and preform genetic correlations of our results with the ‘Big Five’ personality traits, identifying significant correlations with neuroticism, conscientiousness and extraversion. We use the resulting summary statistics to create LDpred-inf polygenic risk scores in UK biobank identifying several brain metrics and regions associate with genetic loading for general happiness level. We also use a novel method to create LDpred-inf polygenic risk scores in two other cohorts, ABCD and Add Health. We found significant correlations with an independent happiness measure in Add Health and nominally significant correlations with several well-being measures in ABCD in both those of European Ancestry and all other ancestries found in these cohorts. We also attempted to replicate our UK Biobank MRi finding in ABCD. We conclude there is evidence that individuals have a general happiness level that is in part genetic which spans across age and ancestry.

Understanding local adaptation has become a key research area given the ongoing climate challenge and the concomitant requirement to conserve genetic resources. Perennial plants, such as forest trees, are good models to study local adaptation given their wide geographic distribution, largely outcrossing mating systems, and demographic histories. We evaluated signatures of local adaptation in European aspen (Populus tremula) across Europe by means of whole-genome resequencing of a collection of 411 individual trees. We dissected admixture patterns between aspen lineages and observed a strong genomic mosaicism in Scandinavian trees, evidencing different colonization trajectories into the peninsula from Russia, Central and Western Europe. As a consequence of the secondary contacts between populations after the last glacial maximum, we detected an adaptive introgression event in a genome region of ∼500 kb in chromosome 10, harboring a large-effect locus that has previously been shown to contribute to adaptation to the short growing seasons characteristic of Northern Scandinavia. Demographic simulations and ancestry inference suggest an Eastern origin—probably Russian—of the adaptive Nordic allele which nowadays is present in a homozygous state at the north of Scandinavia. The strength of introgression and positive selection signatures in this region is a unique feature in the genome. Furthermore, we detected signals of balancing selection, shared across regional populations, that highlight the importance of standing variation as a primary source of alleles that facilitate local adaptation. Our results, therefore, emphasize the importance of migration–selection balance underlying the genetic architecture of key adaptive quantitative traits.

Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene,DCC, associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an r_gof significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception.

This chapter explores the main social and economic consequences of plague between the 1340s and the 1390s. In 1400 England was still not at the forefront of European economic development, but it was beginning to close the gap on the leaders. GDP per head, the proportion of people in non-agricultural employment, and the livestock share of agriculture had all increased irreversibly. Dependence upon the market for basic commodities and manufactures had increased, and population and taxable wealth were spread more equitably across the country, reducing the economic divide between the south-east and the rest of the country. Recent arguments that the European Marriage Pattern (EMP)—one of the main institutional characteristics of the Little Divergence—was established in England soon after the Black Death are assessed on the basis of the economic and demographic evidence. Serfdom had declined quickly and significantly, and the implications of the English experience for our understanding of the decline of European serfdom are explored. The main institutional changes in factor markets in general, and the spread of contractual arrangements in particular, are considered. By 1400 the main changes had worked their way through the economy, and further significant developments did not occur until population began to rise again in the sixteenth century.

Individuals with severe mental illness have an increased risk of cardiometabolic diseases compared to the general population. Shared risk factors and medication effects explain part of this excess risk; however, there is growing evidence to suggest that shared biology (including genetic variation) is likely to contribute to comorbidity between mental and physical illness. Contactins are a family of genes involved in development of the nervous system and implicated, though genome-wide association studies, in a wide range of psychological, psychiatric and cardiometabolic conditions. Contactins are plausible candidates for shared pathology between mental and physical health. We used data from UK Biobank to systematically assess how genetic variation in contactin genes was associated with a wide range of psychological, psychiatric and cardiometabolic conditions. We also investigated whether associations for cardiometabolic and psychological traits represented the same or distinct signals and how the genetic variation might influence the measured traits. We identified: A novel genetic association between variation in CNTN1 and current smoking; two independent signals in CNTN4 for BMI; and demonstrated that associations between CNTN5 and neuroticism were distinct from those between CNTN5 and blood pressure/HbA1c. There was no evidence that the contactin genes contributed to shared aetiology between physical and mental illness

Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome‐wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA‐Seq data that we used to perform gene co‐expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population‐wide co‐expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small‐effect variations in gene expression. Genes associated with shape variation were peripheral within the population‐wide co‐expression network, were not highly connected within the leaf development co‐expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.

Chronic pain is highly prevalent worldwide and imparts significant socioeconomic and public health burden and is more prevalent in women than in men. Factors that influence susceptibility and mechanisms of chronic pain development, are not fully understood. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype in UK Biobank. Genetic correlations between MCP in each sex and a range of psychiatric, autoimmune, and anthropometric phenotypes were examined. The relationship between female and male MCP, and chronic widespread pain was investigated using polygenic risk scoring. Expression of sex-specific MCP-associated loci in a range of tissues was examined using GTEx, and separately in neural and non-neural human tissues with assessment for dorsal-root ganglion (DRG) enrichment. For genes enriched for neural-tissue expression the full GTEx database was queried for sex-differential gene expression in CNS regions, and for high expression in sex-specific tissues. Expression in neural mouse tissue was also examined for orthologs of these genes. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS output found 87 independent SNPs to be significantly associated with MCP. We found sex-specific MCP-associated genes, with 31 genes and 37 genes associated with female and male MCP respectively and one gene associated with MCP in both sexes ( DCC ). We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at r _g significantly less than 1. All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the DRG, and many showed elevated expression in sex-specific tissues. Overall, findings indicate sex differences in chronic pain at the SNP, gene and transcriptomic level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong nervous-system component to chronic pain in both sexes, emphasise the importance of the DRG, and indicate specific loci which may play a specialised role in nociception.

Chronic pain is a complex trait that is moderately heritable and genetically, as well as phenotypically, correlated with major depressive disorder (MDD). Use of the conditional false discovery rate (cFDR) approach, which leverages pleiotropy identified from existing GWAS outputs, has been successful in discovering novel associated variants in related phenotypes. Here, genome-wide association study outputs for both von Korff chronic pain grade and for MDD were used to identify variants meeting a cFDR threshold for each outcome phenotype separately, as well as a conjunctional cFDR (ccFDR) threshold for both phenotypes together. Using a moderately conservative threshold, we identified a total of 11 novel single nucleotide polymorphisms (SNPs), six of which were associated with chronic pain grade and nine of which were associated with MDD. Four SNPs on chromosome 14 were associated with both chronic pain grade and MDD. SNPs associated only with chronic pain grade were located withinSLC16A7on chromosome 12. SNPs associated only with MDD were located either in a gene-dense region on chromosome 1 harbouringLINC01360,LRRIQ3, FPGTandFPGT-TNNI3K, or within/close toLRFN5on chromosome 14. The SNPs associated with both outcomes were also located withinLRFN5. Several of the SNPs on chromosomes 1 and 14 were identified as being associated with expression levels of nearby genes in the brain and central nervous system. Overall, using the cFDR approach, we identified several novel genetic loci associated with chronic pain and we describe likely pleiotropic effects of a recently identified MDD locus on chronic pain.