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Background: Lipoprotein(a) (Lp(a)) is now established as a causal risk factor for cardiovascular disease (CVD) and accurate laboratory measurement is of pivotal importance in reducing Lp(a) associated risk. The consensus statement by HEART UK in 2019 included recommendations to improve standardisation of clinical laboratory measurement and reporting of Lp(a). Methods: A 16 question, electronic audit survey was circulated to 190 accredited clinical biochemistry laboratories to assess the adoption of these recommendations in the UK. Results: Responses were received from 65 of 190 laboratories (34%). Only 5 (8%) did not offer Lp(a) measurement. Of those providing the test, 23% (n = 14) offered an in-house service (IHS), the remaining laboratories (77%; n = 46) used an external referral service (ERS). The majority (10 of 14 or 71%) of IHS laboratories responded with details of their method, stating whether it minimised sensitivity to the effect of Lp(a) isoform size and used calibrators certified for traceability to the WHO/IFCC reference material, however, only a minority ERS laboratories (13 of the 46 or 28%) were able to specify the method used by their referral laboratory. Of the laboratories who specified their reporting units, 6 of 10 IHS and 7 of 23 ERS laboratories reported in nmol/L. Among the 60 laboratories who responded, the HEART UK recommendations appear to have been adopted in full by only 3 IHS laboratories. Conclusions: Further efforts are needed to standardise the measurement and reporting of Lp(a) so that results and interpretation are comparable across clinical biochemistry laboratories in the UK. [ABSTRACT FROM AUTHOR]

Background: Dyslipidaemia is an important cardiovascular risk factor for people with severe mental illness, contributing to premature mortality. The link between antipsychotics and dyslipidaemia is well established, while evidence on antidepressants is mixed. Aims: To investigate if antidepressant/antipsychotic use was associated with lipid parameters in UK Biobank participants and if CYP2C19 and CYP2D6 genetic variation plays a role. Methods: Review of self-reported prescription medications identified participants taking antidepressants/antipsychotics. Total, low-, and high-density lipoprotein cholesterol (L/HDL-C) and triglycerides derived from blood samples. CYP2C19 and CYP2D6 metabolic phenotypes were assigned from genetic data. Linear regression investigated aims, adjusted for key covariates. Results: Of 469,739 participants, 36,043 took antidepressants (53% female, median age 58, 17% taking cholesterol-lowering medications) and 3255 took antipsychotics (58% female, median age 57, 27% taking cholesterol-lowering medications). Significant associations were found between use of each amitriptyline, fluoxetine, citalopram/escitalopram, sertraline, paroxetine and venlafaxine with higher total cholesterol, LDL-C, and triglycerides and lower HDL-C, compared to participants not taking each medication. Venlafaxine was associated with the worst lipid profile (total cholesterol, adjusted mean difference: 0.21 mmol/L, 95% confidence interval (CI): 0.17 to 0.26, p < 0.001). Antipsychotic use was significantly associated with lower HDL-C and higher triglycerides. In participants taking sertraline, CYP2C19 intermediate metabolisers had higher HDL-C (0.05 mmol/L, 95% CI: 0.01 to 0.09, p = 0.007) and lower triglycerides (−0.17 mmol/L, 95% CI: −0.29 to −0.05, p = 0.007), compared to normal metabolisers. Conclusions: Antidepressants were significantly associated with adverse lipid profiles, potentially warranting baseline and regular monitoring. Further research should investigate the mechanistic pathways underlying the protective effects of the CYP2C19 intermediate metaboliser phenotype on HDL-C and triglycerides in people taking sertraline. [ABSTRACT FROM AUTHOR]

Background: Diabetes, obesity and metabolic syndrome are highly prevalent in patients with severe mental illness and can impose a major physical health burden. Objective: To determine how anthropometric and metabolic features changed over time in a retrospective cohort of people with Severe Mental Illness living in Cheshire, UK. Methods: In all, 1307 individuals on the severe mental illness Register were followed up between 2002 and 2012 in UK general practice. Subjects were identified through a pseudanonymised search of general practice registers. Results: Baseline body mass index was 28.6 kg/m2 increasing to 31.0 at 10-year follow-up (r² = 0.84; p = 0.0002). There was a significant increase in fasting blood glucose from 5.72 to 6.79 mmol/L (r² = 0.48; p = 0.026). Correspondingly, there was a strong positive univariate relation between increase in body mass index and fasting blood glucose (r² = 0.54; p < 0.0001) taking into account all measurements. Fasting blood glucose also increased slightly with age (p = 0.028). With increasing use of statins, total cholesterol fell from 4.5 to 3.9 mmol/L (r² = 0.88; p = 0.0001), as did low-density lipoprotein cholesterol from 3.43 to 2.35 mmol/L (r² = 0.94; p = 0.0001). In multivariate models, adjusting for age, gender, smoking and blood pressure, each unit increase in body mass index (odds ratio = 1.07 [1.01, 1.13]; p = 0.031) and triglycerides (odds ratio = 1.28 (1.06, 1.55); p = 0.009) was independently associated with an increased risk of having type 2 diabetes. Conclusion: Increasing body mass index relates to increasing rates of dysglycaemia over time. Measures to encourage weight reduction should be key strategies to reduce dysglycaemia rates in severe mental illness. Prescribing statins may have been effective in improving the lipid profile in this group. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) associates with excess cardiovascular risk and there is a need to assess that risk. However, individual lipid levels may be influenced by disease activity and drug use, whereas lipid ratios may be more robust. A cross-sectional cohort of 400 consecutive patients was used to establish factors that influenced individual lipid levels and lipid ratios in RA, using multiple regression models. A further longitudinal cohort of 550 patients with RA was used to confirm these findings, using generalized estimating equations. Cross-sectionally, higher C-reactive protein (CRP) levels correlated with lower levels of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol ([HDL-C] P ≤ .015), whereas lipid ratios did not correlate with CRP. The findings were broadly replicated in the longitudinal data. In summary, the effects of inflammation on individual lipid levels may underestimate lipid-associated cardiovascular disease (CVD) risk in RA, thus lipid ratios may be more appropriate for CVD risk stratification in RA. [ABSTRACT FROM PUBLISHER]

Background: Targets for cholesterol reduction are part of the Quality Outcomes Framework and general practitioners have to meet these targets to fulfil their remuneration package. By contrast, there are no targets for the accuracy of cholesterol or other lipid measurements and no recent surveys on performance of these assays. We have assessed the performance of lipid measurement of the available methods in the UK. Methods: Serum samples collected from individual donors attending the national blood service were distributed after values were obtained from a secondary reference laboratory. Samples were sent to participant laboratories to assess different methods' analytical performance on single donation specimens, on routine external quality assessment pooled specimens, on specimens subjected to a range of freeze-thaw cycles and on frozen-stored specimens. Results: Differences in measured cholesterol were found that were method-dependent and related to triglyceride content. HDL-cholesterol (HDL-C) showed significant positive bias in all assays. Individual donor specimens showed no significant changes with differing numbers of freeze-thaw cycles. Pooled serum was stable for up to six months. Conclusions: Most cholesterol measurements are accurate but some methods are affected by triglyceride interference. HDL-C methods show significant positive bias. Although there are potential matrix effects introduced as a result of specimen preparation, additional work is needed to show if these effects are present in fresh patient samples. [ABSTRACT FROM AUTHOR]