👤 Yoav Ben-Shlomo

The importance of advance care planning in parkinsonism is increasingly recognised. Existing evidence shows plans are infrequent in this population. Little is known about the details of the plans themselves and whether patient factors predict advance care planning practices. This study aimed to describe advance care planning in people with parkinsonism enrolled in the PRoactive Integrated Management and Empowerment (PRIME-UK) trial, and identify factors associated with advance care planning. This is a cross-sectional substudy of 211 participants within the PRIME-UK randomised controlled trial, a single-centre trial that randomised 214 people with parkinsonism to receive either a novel model of care (PRIME-Parkinson care) or usual care (ISRCTN trial ID 16783200). The presence of a treatment escalation plan was used as a measure of advance care planning. At the time of this study, a quarter (n=53, 25%) of participants had a treatment escalation plan. 45% of plans were created during an emergency hospital admission. 100 participants had appointed a lasting power of attorney (LPA). In adjusted regression models, increasing parkinsonism severity (OR 2.2, 95% CI 1.55 to 3.12), increasing frailty (OR 3.69, 95% CI 1.42 to 9.63) and increasing comorbidity (OR 2.51, 95% CI 1.53 to 4.14) were associated with having a treatment escalation plan. Treatment escalation plans for people with parkinsonism are frequently completed in advanced disease during emergency hospital admission. Many individuals are appointing LPAs, suggesting an interest in future planning that could be further supported by clinicians. Future research should explore interventions to improve proactive outpatient advance care planning. 16783200. Show less

Platelet reactivity, an important factor in hemostasis and chronic disease, has widespread inter-individual variability with a substantial genetic contribution. Previously, our group performed a genome-wide association study of platelet reactivity identifying single nucleotide polymorphisms (SNPs) associated with ADP- and epinephrine- induced aggregation, including SNPs in MRVI1, PIK3CG, JMJD1C, and PEAR1, among others. Here, we assessed the association of these previously identified SNPs with ADP-, thrombin-, and shear- induced platelet aggregation. Additionally, we sought to expand the association of these SNPs with blood cell counts and hemostatic factors. To accomplish this, we examined the association of 12 SNPs with seven platelet reactivity and various hematological measures in 1300 middle-aged men in the Caerphilly Prospective Study. Nine of the examined SNPs showed at least suggestive association with platelet reactivity. The strongest associations were with rs12566888 in PEAR1 to ADP-induced (p = 1.51 × 10(-7)) and thrombin-induced (p = 1.91 × 10(-6)) reactivity in platelet rich plasma. Our results indicate PEAR1 functions in a relatively agonist independent manner, possibly through subsequent intracellular propagation of platelet activation. rs10761741 in JMJD1C showed suggestive association with ADP-induced reactivity (p = 1.35 × 10(-3)), but its strongest associations were with platelet-related cell counts (p = 1.30 × 10(-9)). These associations indicate variation in JMJD1C influences pathways that modulate platelet development as well as those that affect reactivity. Associations with other blood cell counts and hemostatic factors were generally weaker among the tested SNPs, indicating a specificity of these SNPs' function to platelets. Future genome-wide analyses will further assess association of these genes and identify new genes important to platelet biology. Show less

Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations. Show less

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls. Show less