Anxiety disorders and age-related changes in physiology

Background Anxiety disorders are leading contributors to the global disease burden, highly prevalent across the lifespan and associated with substantially increased morbidity and early mortality. Aims The aim of this study was to examine age-related changes across a wide range of physiological measures in middle-aged and older adults with a lifetime history of anxiety disorders compared with healthy controls. Method The UK Biobank study recruited >500 000 adults, aged 37-73, between 2006 and 2010. We used generalised additive models to estimate non-linear associations between age and hand-grip strength, cardiovascular function, body composition, lung function and heel bone mineral density in a case group and in a control group. Results The main data-set included 332 078 adults (mean age 56.37 years; 52.65% women). In both genders, individuals with anxiety disorders had a lower hand-grip strength and lower blood pressure, whereas their pulse rate and body composition measures were higher than in the healthy control group. Case-control group differences were larger when considering individuals with chronic and/or severe anxiety disorders, and differences in body composition were modulated by depression comorbidity status. Differences in age-related physiological changes between females in the anxiety disorder case group and healthy controls were most evident for blood pressure, pulse rate and body composition, whereas this was the case in males for hand-grip strength, blood pressure and body composition. Most differences in physiological measures between the case and control groups decreased with increasing age. Conclusions Findings in individuals with a lifetime history of anxiety disorders differed from a healthy control group across multiple physiological measures, with some evidence of case-control group differences by age. The differences observed varied by chronicity/severity and depression comorbidity

Pharmacogenetic testing through the direct-to-consumer genetic testing company 23andMe.

BACKGROUND: Rapid advances in scientific research have led to an increase in public awareness of genetic testing and pharmacogenetics. Direct-to-consumer (DTC) genetic testing companies, such as 23andMe, allow consumers to access their genetic information directly through an online service without the involvement of healthcare professionals. Here, we evaluate the clinical relevance of pharmacogenetic tests reported by 23andMe in their UK tests. METHODS: The research papers listed under each 23andMe report were evaluated, extracting information on effect size, sample size and ethnicity. A wider literature search was performed to provide a fuller assessment of the pharmacogenetic test and variants were matched to FDA recommendations. Additional evidence from CPIC guidelines, PharmGKB, and Dutch Pharmacogenetics Working Group was reviewed to determine current clinical practice. The value of the tests across ethnic groups was determined, including information on linkage disequilibrium between the tested SNP and causal pharmacogenetic variant, where relevant. RESULTS: 23andMe offers 12 pharmacogenetic tests to their UK customers, some of which are in standard clinical practice, and others which are less widely applied. The clinical validity and clinical utility varies extensively between tests. The variants tested are likely to have different degrees of sensitivity due to different risk allele frequencies and linkage disequilibrium patterns across populations. The clinical relevance depends on the ethnicity of the individual and variability of pharmacogenetic markers. Further research is required to determine causal variants and provide more complete assessment of drug response and side effects. CONCLUSION: 23andMe reports provide some useful pharmacogenetics information, mirroring clinical tests that are in standard use. Other tests are unspecific, providing limited guidance and may not be useful for patients without professional interpretation. Nevertheless, DTC companies like 23andMe act as a powerful intermediate step to integrate pharmacogenetic testing into clinical practice

Risk factor profiles for depression following childbirth or a chronic disease diagnosis:case-control study

BACKGROUND: Progress towards understanding the aetiology of major depression is compromised by its clinical heterogeneity. The variety of contexts underlying the development of a major depressive episode may contribute to such heterogeneity. AIMS: To compare risk factor profiles for three subgroups of major depression according to episode context. METHOD: Using self-report questionnaires and administrative records from the UK Biobank, we characterised three contextual subgroups of major depression: postpartum depression (3581 cases), depression following diagnosis of a chronic disease (409 cases) and a more typical (named heterogeneous) major depression phenotype excluding the two other contexts (34 699 cases). Controls with the same exposure were also defined. We tested each subgroup for association with the polygenic risk scores (PRS) for major depression and with other risk factors previously associated with major depression (bipolar disorder PRS, neuroticism, reported trauma in childhood and adulthood, socioeconomic status, family history of depression, education). RESULTS: Major depression PRS was associated with all subgroups, but postpartum depression cases had higher PRS than heterogeneous major depression cases (OR = 1.06, 95% CI 1.02–1.10). Relative to heterogeneous depression, postpartum depression was more weakly associated with adulthood trauma and neuroticism. Depression following diagnosis of a chronic disease had weaker association with neuroticism and reported trauma in adulthood and childhood relative to heterogeneous depression. CONCLUSIONS: The observed differences in risk factor profiles according to the context of a major depressive episode help provide insight into the heterogeneity of depression. Future studies dissecting such heterogeneity could help reveal more refined aetiological insights

Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane's Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

Stratified genome-wide association analysis of Type 2 Diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane’s Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

Variance components linkage analysis for adjusted systolic blood pressure in the Framingham Heart Study

We performed variance components linkage analysis in nuclear families from the Framingham Heart Study on nine phenotypes derived from systolic blood pressure (SBP). The phenotypes were the maximum and mean SBP, and SBP at age 40, each analyzed either uncorrected, or corrected using two subsets of epidemiological/clinical factors. Evidence for linkage to chromosome 8p was detected with all phenotypes except the uncorrected maximum SBP, suggesting this region harbors a gene contributing to variation in SBP

Genetics of stroke in a UK African ancestry case-control study: South London Ethnicity and Stroke Study.

OBJECTIVE: Despite epidemiologic data showing an increased stroke incidence in African ancestry populations, genetic studies in this group have so far been limited, and there has been little characterization of the genetic contribution to stroke liability in this population, particularly for stroke subtypes. METHODS: We evaluated the evidence that genetic factors contribute to stroke and stroke subtypes in a population of 917 African and African Caribbean stroke cases and 868 matched controls from London, United Kingdom. We (1) estimated the heritability of stroke in this population using genomic-relatedness matrix-restricted maximum likelihood approaches, (2) assessed loci associated with stroke in Europeans in our population, and (3) evaluated the influence of genetic factors underlying cardiovascular risk factors on stroke using polygenic risk scoring. RESULTS: Our results indicate a substantial genetic contribution to stroke risk in African ancestry populations (h2 = 0.35 [SE = 0.19], p = 0.043). Polygenic risk scores indicate that cardiovascular risk scores contribute to the genetic liability (odds ratio [OR] 1.09 [95% confidence interval (CI) 1.01-1.17], p = 0.029) and point to a strong influence of type 2 diabetes in large vessel stroke (OR 1.62 [95% CI 1.19-2.22], p = 0.0024). Single nucleotide polymorphisms associated with ischemic stroke in Europeans shared direction of effect in SLESS (p = 0.031), suggesting that disease mechanisms are shared across ancestries. CONCLUSIONS: Stroke in African ancestry populations is highly heritable and influenced by genetic determinants underlying cardiovascular risk factors. In addition, stroke loci identified in Europeans share direction of effect in African populations. Future genome-wide association studies must focus on incorporating African ancestry individuals

Novel IL10 gene family associations with systemic juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is the most common cause of chronic childhood disability and encompasses a number of disease subgroups. In this study we have focused on systemic JIA (sJIA), which accounts for approximately 11% of UK JIA cases. This study reports the investigation of three members of the IL10 gene family as candidate susceptibility loci in children with sJIA. DNA from 473 unaffected controls and 172 patients with sJIA was genotyped for a single nucleotide polymorphism (SNP) in IL19 and IL20 and two SNPs in IL10. We examined evidence for association of the four SNPs by single marker and haplotype analysis. Significant differences in allele frequency were observed between cases and controls, for both IL10-1082 (p = 0.031) and IL20-468 (p = 0.028). Furthermore, examination of the haplotypes of IL10-1082 and IL20-468 revealed greater evidence for association (global p = 0.0006). This study demonstrates a significant increased prevalence of the low expressing IL10-1082 genotype in patients with sJIA. In addition, we show a separate association with an IL20 polymorphism, and the IL10-1082A/IL20-468T haplotype. The two marker 'A-T' haplotype confers an odds ratio of 2.24 for sJIA. This positive association suggests an important role for these cytokines in sJIA pathogenesis