Influence of autozygosity on common disease risk across the phenotypic spectrum.

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (FROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity

¹H and ¹³C NMR assignments of the three dicyclopenta-fused pyrene congeners

Complete ¹H and ¹³HC NMR assignments of the (di-)cyclopenta-fused pyrene congeners, cyclopenta[cd]- (2), dicyclopenta[cd,fg]- (3), dicyclopenta[cd,jk]- (4) and dicyclopenta[cd,mn]pyrene (5), respectively, are archieved using two-dimensional (2D) NMR spectroscopy. The experimental ¹³C chemical shift assignments are compared with computed ab initio CTOCD-PZ2/6-31G** ¹³C chemical shifts; a satisfactory agreement is found. Substituent-induced chemical shifts in the pyrene core induced by annelation of cyclopenta moieties are discussed. Effects of dicyclopenta topology on electric structure are illustrated for 3-5

A systematic review on the association of the G8 with geriatric assessment, prognosis and course of treatment in older patients with cancer

AIM: The aim of this systematic review is to summarise all available data on the use of the G8 screening tool in geriatric oncology, focusing on the diagnostic accuracy of the G8 to predict the presence of impairments on geriatric assessment (GA) and on its association with different clinical outcomes (survival, course of treatment and patient-centred outcomes). METHODS: A systematic search in MEDLINE and EMBASE for studies on the use of the G8 in older patients with cancer. RESULTS: The literature search identified 8987 reports, of which 54 publications from 46 studies were included (including 18 conference abstracts). 19 studies compared the diagnostic characteristics of the G8 with GA. Median sensitivity and specificity of the G8 for frailty on GA were respectively: 85% and 64%. Out of the 24 studies addressing the association of the G8 with survival, 15 (63%) found the G8 was associated with survival. Six out of fourteen studies (43%) reporting on treatment-related complications found an association between G8 scores and risk of complications. Treatment completion, health care utilisation and patient-centred outcomes were investigated less frequently. CONCLUSION: The G8 is a useful diagnostic tool to identify older patients with cancer who require full GA and is associated with survival and treatment-related complications. Future prospective studies should investigate whether the G8 is predictive for other relevant clinical outcomes such as treatment completion and patient-centred outcomes

Clinical judgment versus geriatric assessment for frailty in older patients with cancer

BACKGROUND: Geriatric assessment (GA) is an appropriate method for identifying frailty in older patients with cancer, but a shorter instrument may be easier to use in clinical practice. Clinical judgment is always available and requires no investments in time or resources. The purpose of this study was to assess correlations between clinical judgment for frailty of the cancer specialist, the general practitioner and patient's self-assessment, and the correlation between clinical judgment and GA. METHODS: This was a dual-center inception cohort study of patients with cancer aged ≥70 years starting curative or first-line palliative chemotherapy. GA included the following domains: (instrumental) activities of daily living, nutrition, mobility, cognition, mood, and polypharmacy. Clinical judgment for frailty was rated on a scale from 0 to 10 (0 = not frail, 10 = frail). Correlation was tested using Kendall's tau-b correlation coefficient. RESULTS: Of all 55 patients, 76% had ≥2 geriatric impairments. Median clinical judgment frailty score was 3 (range 1-10 for cancer specialist and patient and range 0-10 for general practitioner) and did not vary much according to the number of impaired geriatric domains (ranging from 2 for 0-1 impaired domains to 4 for ≥3 impaired domains). Correlations between mutual clinical judgment scores and between clinical judgment and GA were negligible or low. CONCLUSION: Correlations between clinical judgment scores and between clinical judgment and GA were poor. Most patients with multiple geriatric impairments had low 'subjective' frailty scores. Other frailty assessments, such as frailty screening tools or GA, should be considered in addition to clinical judgment when selecting older patients for potential treatment with chemotherapy

Reasons for guideline non-adherence in older and younger women with advanced stage ovarian cancer

Objective: This study aims to assess the reasons for guideline non-adherence in women with advanced stage ovarian cancer and whether these reasons differ according to age. Methods: All women diagnosed with advanced stage ovarian cancer, International Federation of Gynecology and Obstetrics (FIGO) IIb–IV, between 2015 and 2018 were selected from the Netherlands Cancer Registry. Treatment patterns and reasons for guideline non-adherence were analyzed according to age groups. Results: 4210 women were included, of whom 34%, 33%, 26%, and 8% were aged <65, 65–75, 75–85, and ≥85 years respectively. With advancing age, less women received guideline-adherent treatment (decreasing from 70% to 2% in women aged <65 and ≥85 years respectively) and more women received best supportive care only (ranging from 4% to 69% in women aged <65 and ≥85 years respectively). The most prevalent reasons for guideline non-adherence differed according to age and included patient preference in older women, and functional status and extent of disease in younger women. Conclusions: Most older women did not receive guideline-adherent care and patient preference was the most common reason for this decision. This knowledge provides insight in the current treatment decision-making process and highlights the importance of eliciting patient treatment preferences. Further prospective research is necessary to study the underlying motivation for women to decline guideline care and the extent to which shared decision-making influences treatment choice

Disentangling Genetic Risks for Metabolic Syndrome

A quarter of the world's population is estimated to meet the criteria for metabolic syndrome (MetS), a cluster of cardiometabolic risk factors that promote development of coronary artery disease and type 2 diabetes, leading to increased risk of premature death and significant health costs. In this study we investigate whether the genetics associated with MetS components mirror their phenotypic clustering. A multivariate approach that leverages genetic correlations of fasting glucose, HDL cholesterol, systolic blood pressure, triglycerides, and waist circumference was used, which revealed that these genetic correlations are best captured by a genetic one factor model. The common genetic factor genome-wide association study (GWAS) detects 235 associated loci, 174 more than the largest GWAS on MetS to date. Of these loci, 53 (22.5%) overlap with loci identified for two or more MetS components, indicating that MetS is a complex, heterogeneous disorder. Associated loci harbor genes that show increased expression in the brain, especially in GABAergic and dopaminergic neurons. A polygenic risk score drafted from the MetS factor GWAS predicts 5.9% of the variance in MetS. These results provide mechanistic insights into the genetics of MetS and suggestions for drug targets, especially fenofibrate, which has the promise of tackling multiple MetS components

Disentangling Genetic Risks for Metabolic Syndrome

A quarter of the world's population is estimated to meet the criteria for metabolic syndrome (MetS), a cluster of cardiometabolic risk factors that promote development of coronary artery disease and type 2 diabetes, leading to increased risk of premature death and significant health costs. In this study we investigate whether the genetics associated with MetS components mirror their phenotypic clustering. A multivariate approach that leverages genetic correlations of fasting glucose, HDL cholesterol, systolic blood pressure, triglycerides, and waist circumference was used, which revealed that these genetic correlations are best captured by a genetic one factor model. The common genetic factor genome-wide association study (GWAS) detects 235 associated loci, 174 more than the largest GWAS on MetS to date. Of these loci, 53 (22.5%) overlap with loci identified for two or more MetS components, indicating that MetS is a complex, heterogeneous disorder. Associated loci harbor genes that show increased expression in the brain, especially in GABAergic and dopaminergic neurons. A polygenic risk score drafted from the MetS factor GWAS predicts 5.9% of the variance in MetS. These results provide mechanistic insights into the genetics of MetS and suggestions for drug targets, especially fenofibrate, which has the promise of tackling multiple MetS components