A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

Physical functioning and symptoms of chronic fatigue in sarcoidosis patients

Scientific reports underscore the importance of measuring the health-related quality of life in sarcoidosis patients. The present study seeks to define how sarcoidosis patients’ quality of life, daily physical activity, and physical performance are related to each other. Seventeen patients (mean age 46.8 ± 8.8 years) suffering from sarcoidosis completed the following questionnaires: the fatigue assessment scale (FAS), the quality of life scale (SF-36 questionnaire), and the Borg dyspnea scale. Physical activity (PA) was assessed using accelerometry. Respiratory function, consisting of forced expiratory volume in one second (FEV1), forced vital capacity (FVC), forced expiratory volume in one second as a percentage of vital capacity (FEV1/%FVC), and diffusing capacity of the lungs for carbon monoxide (DLCO), were assessed. In addition, performance in 6-min walk test (MWT), aerobic capacity assessed from maximal oxygen uptake (VO2max), and the metabolic equivalent of task (MET) were evaluated. We found that daily PA (4566 ± 2378 steps/day) and VO2max (21.8 ± 5.9 ml/kg/min) were lower in sarcoidosis patients than the known predicted values in healthy age-matched individuals. There were significant inverse associations between the FAS score and 6MWT (r = −0.62; p < 0.01), and between SF-36 score and 6MWT (r = −0.55; p < 0.03). In contrast, SF-36 scores associated with fatigue and dyspnea scores (r = 0.72; p < 0.001 and r = 0.85; p < 0.001). These findings imply that sarcoidosis patients are less active compared with healthy subjects. The FAS and SF-36 scales seem to be effective tools for assessing the severity of fatigue in sarcoidosis patients

Disease Burden and Variability in Sarcoidosis

Sarcoidosis is a systemic inflammatory disease with substantial morbidity and increasing mortality. As part of the National Heart, Lung, and Blood Institute's workshop to better understand this disease and improve the outcomes of patients with sarcoidosis, we reviewed the available data on health care burden and outcomes of this disease in the United States. Disparities in outcomes exist by race, ethnicity, sex, and socioeconomic groups, with African Americans having disproportionately more severe disease. Mortality rates are highest in African Americans, but may be increasing in white individuals. The health care burden of sarcoidosis is defined not only by its somatic manifestations, but is also greatly impacted by psychosocial, economic, and comorbid conditions associated with this disease. Fatigue, depression, cognitive dysfunction, treatment side effects, and pain syndromes are highly prevalent in this population and contribute to poor outcomes. The direct and indirect economic costs to patients and society are likely also substantial, although not well defined. We recommend leveraging existing and future technology and infrastructure to more accurately define and monitor the overall total sarcoidosis-attributable health care burden and patient outcomes in the United States

A predictive tool for an effective use of ¹⁸F-FDG PET in assessing activity of sarcoidosis

<p>Abstract</p> <p>Background</p> <p>¹⁸F-FDG PET/CT (PET) is useful in assessing inflammatory activity in sarcoidosis. However, no appropriate indications are available. The aim of this study was to develop a prediction rule that can be used to identify symptomatic sarcoidosis patients who have a high probability of PET-positivity.</p> <p>Methods</p> <p>We retrospectively analyzed a cohort of sarcoidosis patients with non organ specific persistent disabling symptoms (n = 95). Results of soluble interleukin-2 receptor (sIL-2R) assessment and high-resolution computed tomography (HRCT) were included in the predefined model. HRCT scans were classified using a semi-quantitative scoring system and PET findings as positive or negative, respectively. A prediction model was derived based on logistic regression analysis. We quantified the model’s performance using measures of discrimination and calibration. Finally, we constructed a prediction rule that should be easily applicable in clinical practice.</p> <p>Results</p> <p>The prediction rule showed good calibration and good overall performance (goodness-of-fit test, p = 0.78, Brier score 20.1%) and discriminated between patients with positive and negative PET findings (area under the receiver-operating characteristic curve, 0.83). If a positive predictive value for the presence of inflammatory activity of ≥90% is considered acceptable for clinical decision-making without referral to PET, PET would be indicated in only 29.5% of the patients. Using a positive predictive value of 98%, about half of the patients (46.3%) would require referral to PET.</p> <p>Conclusions</p> <p>The derived and internally validated clinical prediction rule, based on sIL-2R levels and HRCT scoring results, appeared to be useful to identify sarcoidosis patients with a high probability of inflammatory activity. Using this rule may enable a more effective use of PET scan for assessment of inflammatory activity in sarcoidosis.</p