Search

Objective Biomarkers for diagnosis and progression of osteoarthritis (OA) are lacking. This study was undertaken to identify circulating biomarkers for OA that could predict disease occurrence and/or progression to joint replacement. Methods Using the SomaScan platform, we measured 4,792 proteins in plasma from 37,278 individuals, of whom 12,178 individuals had OA and 2,524 had undergone joint replacement. We performed a case-control study for identification of potential protein biomarkers for hip, knee, and/or hand OA, and a prospective study for identification of biomarkers for joint replacement. Results Among the large panel of plasma proteins assessed, cartilage acidic protein 1 (CRTAC1) was the most strongly associated with both OA diagnosis (odds ratio 1.46 [95% confidence interval 1.41-1.52] for knee OA, odds ratio 1.36 [95% confidence interval 1.29-1.43] for hip OA, and odds ratio 1.33 [95% confidence interval 1.26-1.40] for hand OA) and progression to joint replacement (hazard ratio 1.40 [95% confidence interval 1.30-1.51] for knee replacement and hazard ratio 1.31 [95% confidence interval 1.19-1.45] for hip replacement). Patients with OA who were in the highest quintile of risk of joint replacement, based on known risk factors (i.e., age, sex, and body mass index) and plasma CRTAC1 level, were 16 times more likely to undergo knee replacement within 5 years of plasma sample collection than those in the lowest quintile, and 6.5 times more likely to undergo hip replacement. CRTAC1 was not associated with other types of inflammatory arthritis. A specific protein profile was identified in those patients who had undergone joint replacement prior to plasma sample collection. Conclusion Through a hypothesis-free approach, we identified CRTAC1 in plasma as a novel promising candidate biomarker for OA that is both associated with occurrence of OA and predictive of progression to joint replacement. This biomarker might also be useful in the selection of suitable patients for clinical trial enrollment.

The authors have withdrawn this manuscript because this paper was posted prematurely in advance of a UK Biobank Pharma Proteomics Project consortium effort. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author

Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation., Bell et al. report 46 new loci associated with biomarkers of iron homeostasis, including ferritin levels, iron binding capacity, and iron saturation, in the Icelandic, Danish and UK populations. The associated loci point to new iron-regulating proteins and important genetic differences between men and women.

The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF)

About 5-8% of individuals over the age of 60 have dementia. With our ever-aging population this number is likely to increase, making dementia one of the most important threats to public health in the 21st century. Given the phenotypic overlap of individual dementias the diagnosis of dementia is a major clinical challenge, even with current gold standard diagnostic approaches. However, it has been shown that certain dementias show specific structural characteristics in the brain. Progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) are prototypical examples of this phenomenon, as they often present with characteristic brainstem atrophy. More detailed characterization of brain atrophy due to individual diseases is urgently required to select biomarkers and therapeutic targets that are meaningful to each disease. Here we present a joint multi-atlas-segmentation and deep-learning-based segmentation method for fast and robust parcellation of the brainstem into its four sub-structures, i.e., the midbrain, pons, medulla, and superior cerebellar peduncles (SCP), that in turn can provide detailed volumetric information on the brainstem sub-structures affected in PSP and MSA. The method may also benefit other neurodegenerative diseases, such as Parkinson's disease; a condition which is often considered in the differential diagnosis of PSP and MSA. Comparison with state-of-the-art labeling techniques evaluated on ground truth manual segmentations demonstrate that our method is significantly faster than prior methods as well as showing improvement in labeling the brainstem indicating that this strategy may be a viable option to provide a better characterization of the brainstem atrophy seen in PSP and MSA., Accepted to SPIE Medical Imaging 2021

Publisher's version (útgefin grein). Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations., Discovery of coding variants in genes that confer risk of neurodevelopmental disorders is an important step towards understanding the pathophysiology of these disorders. Wholegenome sequencing of 31,463 Icelanders uncovers a frameshift variant (E712KfsTer10) in microtubule-associated protein 1B (MAP1B) that associates with ID/low IQ in a large pedigree (genome-wide corrected P = 0.022). Additional stop-gain variants in MAP1B (E1032Ter and R1664Ter) validate the association with ID and IQ. Carriers have 24% less white matter (WM) volume (β = −2.1SD, P = 5.1 × 10−8), 47% less corpus callosum (CC) volume (β = −2.4SD, P = 5.5 × 10−10) and lower brain-wide fractional anisotropy (P = 6.7 × 10−4). In summary, we show that loss of MAP1B function affects general cognitive ability through a profound, brain-wide WM deficit with likely disordered or compromised axons., We are grateful to the participants and we thank the psychologists, nurses and staff, in particular Berglind Eiriksdottir, at the Research Recruitment Center and technicians and staff at Röntgen Domus. We also thank the staff at deCODE genetics core facilities and all our colleagues for their important contribution to this work. L.J. received support from the Swedish Society of Medicine, the Swedish Brain Foundation and Swedish Society for Medical Research. The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreements’ no. 115008 (NEWMEDS) and no. 115300 (EUAIMS) of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007-2013), EU-FP7 funded grant no. 602450 (IMAGEMEND) and EU funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC).