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Importance The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. Objective To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. Data Sources Genomewide association studies (GWAS) published up to January 15, 2015. Study Selection GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. Data Extraction and Synthesis Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. Main Outcomes and Measures Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. Results Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]). Conclusions and Relevance It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Importance and study objective The COVID-19 pandemic has produced unprecedented changes in social, work, and leisure activities, which all have had major impact on sleep and psychological well-being. This study documented the prevalence of clinical cases of insomnia, anxiety, and depression and selected risk factors (COVID-19, confinement, financial burden, social isolation) during the first wave of the pandemic in 13 countries throughout the world. Design and participants International, multi-center, harmonized survey of 22 330 adults (mean age = 41.9 years old, range 18–95; 65.6% women) from the general population in 13 countries and four continents. Participants were invited to complete a standardized web-based survey about sleep and psychological symptoms during the first wave of the COVID-19 pandemic from May to August 2020. Results Clinical insomnia symptoms were reported by 36.7% (95% CI, 36.0–37.4) of respondents and 17.4% (95% CI, 16.9–17.9) met criteria for a probable insomnia disorder. There were 25.6% (95% CI, 25.0–26.2) with probable anxiety and 23.1% (95% CI, 22.5–23.6) with probable depression. Rates of insomnia symptoms (>40%) and insomnia disorder (>25%) were significantly higher in women, younger age groups, and in residents of Brazil, Canada, Norway, Poland, USA, and United Kingdom compared to residents from Asian countries (China and Japan, 8% for disorder and 22%–25% for symptoms) (all Ps < 0.01). Proportions of insomnia cases were significantly higher among participants who completed the survey earlier in the first wave of the pandemic relative to those who completed it later. Risks of insomnia were higher among participants who reported having had COVID-19, who reported greater financial burden, were in confinement for a period of four to five weeks, and living alone or with more than five people in same household. These associations remained significant after controlling for age, sex, and psychological symptoms. Conclusion and relevance Insomnia, anxiety, and depression were very prevalent during the first wave of the COVID-19 pandemic. Public health prevention programs are needed to prevent chronicity and reduce long-term adverse outcomes associated with chronic insomnia and mental health problems.

BackgroundQuantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2 × Nanhuizao, F5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified.ResultsIn total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7% - 35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean.ConclusionsHerein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1086) contains supplementary material, which is available to authorized users.