Abstract Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Results: Over two hundred new biomarker-related papers were published during the literature search period. Some papers identified new biomarkers whereas others explored the biological properties and clinical utility of existing markers. There were specific references to several adipocytokines including leptin and adiponectin. ADAM Metallopeptidase with Thrombospondin Type 1 motif 4 (ADAMTS-4) and aggrecan ARGS neo-epitope fragment (ARGS) in synovial fluid (SF) and plasma chemokine (CeC motif) ligand 3 (CCL3) were reported as potential new knee biomarkers. New and refined proteomic technologies and novel assays including a fluoro-microbead guiding chip (FMGC) for measuring C-telopeptide of type II collagen (CTX-II) in serum and urine and a novel magnetic nanoparticle-based technology (termed magnetic capture) for collecting and concentrating CTX-II, were described this past year. Conclusion: There has been steady progress in osteoarthritis (OA) biomarker research in 2016. Several novel biomarkers were identified and new technologies have been developed for measuring existing biomarkers. However, there has been no "quantum leap" this past year and identification of novel early OA biomarkers remains challenging. During the past year, OARSI published a set of recommendations for the use of soluble biomarkers in clinical trials, which is a major step forward in the clinical use of OA biomarkers and bodes well for future OA biomarker development.

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others.Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and highdensity lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

Objectives The aim of this study was to identify sex-specific prevalence and strength of risk factors for the incidence of radiographic knee osteoarthritis (incRKOA). Methods Our study population consisted of 10,958 Rotterdam Study participants free of knee OA in one/both knees at baseline. 1064 participants developed RKOA after a median follow-up time of 9.6 years. We estimated the association between each available risk factor and incRKOA using sex stratified multivariate regression models with generalized estimating equations. Subsequently, we statistically tested sex differences between risk estimates and calculated the population attributable fractions (PAFs) for modifiable risk factors. Results The prevalence of the investigated risk factors was, in general, higher in women compared to men, except alcohol intake and smoking was higher in men and high BMI showed equal prevalence. We found significantly different risk estimates between men and women: high level of PA (RR 1.76, 95% CI 1.29-2.40) or a KL-score 1 at baseline (RR 5.48, 95% CI 4.51-6.65) was higher in men. Among borderline significantly different risk estimates was BMI ≥27, associated with higher risk for incRKOA in women (RR 2.00, 95% CI 1.74-2.31). The PAF for higher BMI was 25.6% in women and 19.3% in men. Conclusion We found sex-specific differences in both presence and relative risks of several risk factors for incRKOA. Especially BMI, a modifiable risk factor, impacts women more strongly than men. These risk factors can be used in the development of personalized prevention strategies and in building sex-specific prediction tools to identify high-risk profile patients.

Objectives The aim of this study was to identify biomarkers for radiographic osteoarthritis severity and progression acting within the inflammation and metabolic pathways. Methods For 3,517 Rotterdam Study participants, 184 plasma protein levels were measured using Olink inflammation and cardiometabolic panels. We studied associations with severity and progression of knee, hip, hand osteoarthritis, and a composite overall OA burden-score by multivariable regression models, adjusting for age, sex, cell counts and BMI. Results We found 18 significantly associated proteins for overall osteoarthritis burden, of which 5 stayed significant after multiple testing correction: circulating Cartilage acidic protein 1 (CRTAC1), Cartilage oligomeric matrix protein (COMP), Thrombospondin 4 (THBS4), Interleukin 18 receptor 1 (IL18R1) and Tumor necrosis factor ligand superfamily member 14 (TNFSF14). These proteins were also associated with progression of knee OA, with the exception of IL18R1. The strongest association was found for the level of CRTAC1 with 1 SD increase in protein level resulting in an increase of 0.09 (95%CI : 0.06–0.12) in overall osteoarthritis KLsum-score (p= 2.9x10−8), in the model adjusted for age, sex, BMI and cell counts. This association was also present with severity of osteoarthritis in all three joints, progression of knee osteoarthritis and was independent of BMI. We observed a stronger association for CRTAC1 with osteoarthritis than for the well-known osteoarthritis-biomarker COMP. Conclusion We identified several compelling biomarkers reflecting overall osteoarthritis burden and increased risk for osteoarthritis progression. CRTAC1 was the most compelling and robust biomarker for osteoarthritis severity and progression. Such a biomarker may be used for disease monitoring.