Circadian Variation in the Response to Vaccination: A Systematic Review and Evidence Appraisal.

Molecular timing mechanisms known as circadian clocks drive endogenous 24-h rhythmicity in most physiological functions, including innate and adaptive immunity. Consequently, the response to immune challenge such as vaccination might depend on the time of day of exposure. This study assessed whether the time of day of vaccination (TODV) is associated with the subsequent immune and clinical response by conducting a systematic review of previous studies. The Cochrane Library, PubMed, Google, Medline, and Embase were searched for studies that reported TODV and immune and clinical outcomes, yielding 3114 studies, 23 of which met the inclusion criteria. The global severe acute respiratory syndrome coronavirus 2 vaccination program facilitated investigation of TODV and almost half of the studies included reported data collected during the COVID-19 pandemic. There was considerable heterogeneity in the demography of participants and type of vaccine, and most studies were biased by failure to account for immune status prior to vaccination, self-selection of vaccination time, or confounding factors such as sleep, chronotype, and shiftwork. The optimum TODV was concluded to be afternoon (5 studies), morning (5 studies), morning and afternoon (1 study), midday (1 study), and morning or late afternoon (1 study), with the remaining 10 studies reporting no effect. Further research is required to understand the relationship between TODV and subsequent immune outcome and whether any clinical benefit outweighs the potential effect of this intervention on vaccine uptake.

Mendelian randomization analysis using GWAS and eQTL data to investigate the relationship between chronotype and neuropsychiatric disorders and their molecular basis.

Chronotype is a proxy sleep measure that has been associated with neuropsychiatric disorders. By investigating how chronotype influences risk for neuropsychiatric disorders and vice versa, we may identify modifiable risk factors for each phenotype. Here we used Mendelian randomization (MR), to explore causal effects by (1) studying the causal relationships between neuropsychiatric disorders and chronotype and (2) characterizing the genetic components of these phenotypes. Firstly, we investigated if a causal role exists between five neuropsychiatric disorders and chronotype using the largest genome-wide association studies (GWAS) available. Secondly, we integrated data from expression quantitative trait loci (eQTLs) to investigate the role of gene expression alterations on these phenotypes. Evening chronotype was causal for increased risk of schizophrenia and autism spectrum disorder and schizophrenia was causal for a tendency toward evening chronotype. We identified 12 eQTLs where gene expression changes in brain or blood were causal for one of the phenotypes, including two eQTLs for SNX19 in hippocampus and hypothalamus that were causal for schizophrenia. These findings provide important evidence for the complex, bidirectional relationship that exists between a sleep-based phenotype and neuropsychiatric disorders, and use gene expression data to identify causal roles for genes at associated loci.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships.

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

Brief Report: Evaluating the Diagnostic Yield of Commercial Gene Panels in Autism.

Autism is a prevalent neurodevelopmental condition, highly heterogenous in both genotype and phenotype. This communication adds to existing discussion of the heterogeneity of clinical sequencing tests, "gene panels", marketed for application in autism. We evaluate the clinical utility of available gene panels based on existing genetic evidence. We determine that diagnostic yields of these gene panels range from 0.22% to 10.02% and gene selection for the panels is variable in relevance, here measured as percentage overlap with SFARI Gene and ranging from 15.15% to 100%. We conclude that gene panels marketed for use in autism are currently of limited clinical utility, and that sequencing with greater coverage may be more appropriate.

Susceptibility to the common cold virus is associated with day length.

Seasonal rhythms are endogenous timing mechanisms that allow animals living at temperate latitudes to synchronize their physiology to the seasons. Human viral respiratory disease is prevalent in the winter at temperate latitudes, but the role of endogenous mechanisms in these recurring annual patterns is unclear. The Common Cold Project is a repository of data describing the experimental viral challenge of 1,337 participants across the seasons of the year. We report a secondary analysis of these data to investigate if susceptibility to the common cold is associated with day length. The majority of the participants (78%) showed signs of infection but only 32% developed clinical signs of disease, and the probability of infection was significantly higher in longer day lengths (summer), but the disease was more likely in short (winter) day lengths. The persistence of winter disease patterns in experimental conditions supports the role of endogenous seasonality in human susceptibility to viral infection.

How does genetic variation modify ND-CNV phenotypes?

Rare copy-number variants (CNVs) associated with neurodevelopmental disorders (NDDs), i.e., ND-CNVs, provide an insight into the neurobiology of NDDs and, potentially, a link between biology and clinical outcomes. However, ND-CNVs are characterised by incomplete penetrance resulting in heterogeneous carrier phenotypes, ranging from non-affected to multimorbid psychiatric, neurological, and physical phenotypes. Recent evidence indicates that other variants in the genome, or 'other hits', may partially explain the variable expressivity of ND-CNVs. These may be other rare variants or the aggregated effects of common variants that modify NDD risk. Here we discuss the recent findings, current questions, and future challenges relating to other hits research in the context of ND-CNVs and their potential for improved clinical diagnostics and therapeutics for ND-CNV carriers.

Autism spectrum disorder genomics: The progress and potential of genomic technologies.

Genomic technologies have accelerated research progress in autism spectrum disorder (ASD) genomics and promises to further transform our understanding of the genetic basis of this neurodevelopmental disorder. Here we review the current evidence for the genetic basis of ASD, present the progress of large-scale studies to date and highlight the potential of genomic technologies. In particular, we discuss evidence for the importance of identifying rare genetic variants in family-based studies. Genomics is a key feature of future healthcare and our review illustrates it's potential to improve our biological understanding of neurodevelopmental disorders, and to ultimately aid ASD diagnosis, inform medical decision making and establish genomics as central to personalised medicine.

Blood-Based Protein Changes in Childhood Are Associated With Increased Risk for Later Psychotic Disorder: Evidence From a Nested Case-Control Study of the ALSPAC Longitudinal Birth Cohort.

The identification of early biological changes associated with the psychotic disorder (PD) is important as it may provide clues to the underlying pathophysiological mechanisms. We undertook the first proteomic profiling of blood plasma samples of children who later develop a PD. Participants were recruited from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who also participated in psychiatric assessment interviews at age 18. Protein expression levels at age 11 were compared between individuals who developed PD at age 18 (n = 37) with population-based age-matched controls (n = 38). Sixty out of 181 plasma proteins profiled were found to be differentially expressed (P < .05) in children with an outcome of the PD. Thirty-four of these proteins were found to be differentially expressed following correction for multiple comparisons. Pathway analysis implicated the complement and coagulation cascade. A second, targeted proteomic approach was used to verify these findings in age 11 plasma from subjects who reported psychotic experiences at age 18 (n = 40) in comparison to age-matched controls (n = 66). Our findings indicate that the complement and coagulation system is dysregulated in the blood during childhood before the development of the PD.

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA. Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study.

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Differential expression of the inflammation marker IL12p40 in the at-risk mental state for psychosis: a predictor of transition to psychotic disorder?

BACKGROUND: The identification of biomarkers of transition from the at-risk mental state (ARMS) to psychotic disorder is important because early treatment of psychosis is associated with improved outcome. Increasing evidence points to an inflammatory contribution to psychosis. We questioned whether raised levels of plasma inflammatory markers predict transition from ARMS to psychotic disorder and whether any such predictors could be reduced by omega-3 (ω-3) polyunsaturated fatty acids (PUFAs). METHODS: We measured the levels of 40 neuroinflammation biomarkers using a commercially available immunoassay kit. Firstly, we compared inflammatory markers in subjects in the ARMS who transitioned to psychotic disorder (n = 11) compared to subjects who did not (n = 28). Then we compared inflammatory markers in all subjects before and after ω-3 PUFA treatment (n = 40). RESULTS: Our data provides preliminary evidence that elevations in the baseline plasma levels of the inflammatory marker IL12/IL23p40 are associated with transition from ARMS to psychotic disorder. IL12/IL23p40 levels did not change following 12 weeks administration of ω-3 PUFAs. These findings provide evidence that elevated plasma IL12/IL23p40 is a potential biomarker of increased risk for transition to psychotic disorder. CONCLUSION: Further studies are required to confirm and extend this finding. Our results do not provide support for the possibility that administration of ω-3 PUFAs act to reduced transition to psychotic disorder by reducing blood levels of IL12/IL23p40. TRIAL REGISTRATION: ClinicalTrials.gov, a service of the U.S. National Institutes of Health, Identifier: NCT00396643 , last updated December 20, 2007. Retrospectively registered.

Genome-wide association studies identify genetic loci for low von Willebrand factor levels.

Low von Willebrand factor (VWF) levels are associated with bleeding symptoms and are a diagnostic criterion for von Willebrand disease, the most common inherited bleeding disorder. To date, it is unclear which genetic loci are associated with reduced VWF levels. Therefore, we conducted a meta-analysis of genome-wide association studies to identify genetic loci associated with low VWF levels. For this meta-analysis, we included 31 149 participants of European ancestry from 11 community-based studies. From all participants, VWF antigen (VWF:Ag) measurements and genome-wide single-nucleotide polymorphism (SNP) scans were available. Each study conducted analyses using logistic regression of SNPs on dichotomized VWF:Ag measures (lowest 5% for blood group O and non-O) with an additive genetic model adjusted for age and sex. An inverse-variance weighted meta-analysis was performed for VWF:Ag levels. A total of 97 SNPs exceeded the genome-wide significance threshold of 5 × 10(-8) and comprised five loci on four different chromosomes: 6q24 (smallest P-value 5.8 × 10(-10)), 9q34 (2.4 × 10(-64)), 12p13 (5.3 × 10(-22)), 12q23 (1.2 × 10(-8)) and 13q13 (2.6 × 10(-8)). All loci were within or close to genes, including STXBP5 (Syntaxin Binding Protein 5) (6q24), STAB5 (stabilin-5) (12q23), ABO (9q34), VWF (12p13) and UFM1 (ubiquitin-fold modifier 1) (13q13). Of these, UFM1 has not been previously associated with VWF:Ag levels. Four genes that were previously associated with VWF levels (VWF, ABO, STXBP5 and STAB2) were also associated with low VWF levels, and, in addition, we identified a new gene, UFM1, that is associated with low VWF levels. These findings point to novel mechanisms for the occurrence of low VWF levels.

Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation.

Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P<5 × 10(-8)) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.

Multiethnic genome-wide association study of cerebral white matter hyperintensities on MRI.

BACKGROUND: The burden of cerebral white matter hyperintensities (WMH) is associated with an increased risk of stroke, dementia, and death. WMH are highly heritable, but their genetic underpinnings are incompletely characterized. To identify novel genetic variants influencing WMH burden, we conducted a meta-analysis of multiethnic genome-wide association studies. METHODS AND RESULTS: We included 21 079 middle-aged to elderly individuals from 29 population-based cohorts, who were free of dementia and stroke and were of European (n=17 936), African (n=1943), Hispanic (n=795), and Asian (n=405) descent. WMH burden was quantified on MRI either by a validated automated segmentation method or a validated visual grading scale. Genotype data in each study were imputed to the 1000 Genomes reference. Within each ethnic group, we investigated the relationship between each single-nucleotide polymorphism and WMH burden using a linear regression model adjusted for age, sex, intracranial volume, and principal components of ancestry. A meta-analysis was conducted for each ethnicity separately and for the combined sample. In the European descent samples, we confirmed a previously known locus on chr17q25 (P=2.7×10(-19)) and identified novel loci on chr10q24 (P=1.6×10(-9)) and chr2p21 (P=4.4×10(-8)). In the multiethnic meta-analysis, we identified 2 additional loci, on chr1q22 (P=2.0×10(-8)) and chr2p16 (P=1.5×10(-8)). The novel loci contained genes that have been implicated in Alzheimer disease (chr2p21 and chr10q24), intracerebral hemorrhage (chr1q22), neuroinflammatory diseases (chr2p21), and glioma (chr10q24 and chr2p16). CONCLUSIONS: We identified 4 novel genetic loci that implicate inflammatory and glial proliferative pathways in the development of WMH in addition to previously proposed ischemic mechanisms.

Genes from a translational analysis support a multifactorial nature of white matter hyperintensities.

BACKGROUND AND PURPOSE: White matter hyperintensities (WMH) of presumed vascular origin increase the risk of stroke and dementia. Despite strong WMH heritability, few gene associations have been identified. Relevant experimental models may be informative. METHODS: We tested the associations between genes that were differentially expressed in brains of young spontaneously hypertensive stroke-prone rats and human WMH (using volume and visual score) in 621 subjects from the Lothian Birth Cohort 1936 (LBC1936). We then attempted replication in 9361 subjects from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). We also tested the subjects from LBC1936 for previous genome-wide WMH associations found in subjects from CHARGE. RESULTS: Of 126 spontaneously hypertensive stroke-prone rat genes, 10 were nominally associated with WMH volume or score in subjects from LBC1936, of which 5 (AFP, ALB, GNAI1, RBM8a, and MRPL18) were associated with both WMH volume and score (P<0.05); 2 of the 10 (XPNPEP1, P=6.7×10(-5); FARP1, P=0.024) plus another spontaneously hypertensive stroke-prone rat gene (USMG5, P=0.00014), on chromosomes 10, 13, and 10 respectively, were associated with WMH in subjects from CHARGE. Gene set enrichment showed significant associations for downregulated spontaneously hypertensive stroke-prone rat genes with WMH in humans. In subjects from LBC1936, we replicated CHARGE's genome-wide WMH associations on chromosomes 17 (TRIM65 and TRIM47) and, for the first time, 1 (PMF1). CONCLUSIONS: Despite not passing multiple testing thresholds individually, these genes collectively are relevant to known WMH associations, proposed WMH mechanisms, or dementia: associations with Alzheimer's disease, late-life depression, ATP production, osmotic regulation, neurodevelopmental abnormalities, and cognitive impairment. If replicated further, they suggest a multifactorial nature for WMH and argue for more consideration of vascular contributions to dementia.

Genome-wide association analysis identifies six new loci associated with forced vital capacity.

Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling.

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects.

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8). This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.