👤 Mischa Lundberg

Muscular strength is a marker of current health and a predictor of long-term health outcomes in young populations, supporting the inclusion of muscle-strengthening activities into current guidelines and recommendations. Over the last decade, muscular strength has been included in several fitness-test batteries in children and adolescents. However, little is known about its relevance and the feasibility of assessing it in preschool children aged 3-5 years. Therefore, in this cross-sectional study, we aimed to generate reference values for handgrip strength in Swedish preschool children and to examine the associations of device-measured movement behaviours (sedentary time [ST], light physical activity [LPA], moderate-to-vigorous physical activity [MVPA], and sleep duration) with handgrip strength using compositional data analysis. A total of 3,218 preschool children (48.53% female) aged 3.0-5.5 years from Sweden were included. Handgrip strength was measured using a validated analog dynamometer following standardized procedures. Movement behaviours were assessed in a subsample of 2,328 children who had both handgrip data and valid accelerometer recordings. Compositional data analysis was used to examine associations between handgrip strength and the 24-hour time-use composition, adjusting for age, sex, body mass index, parental education, and wear time. Age- and sex-specific percentiles for handgrip strength were developed. Boys showed higher handgrip values than girls at all ages (e.g., median increased from 4.08 to 7.42 kg in boys and from 3.45 to 6.87 kg in girls between ages 3 and 5 years). When the proportion of time spent in MVPA increased relative to the other behaviours, handgrip strength rose by + 1.22 kg; the opposite was observed for ST, which related to - 0.84 kg lower handgrip strength. No significant associations were observed for LPA or sleep duration (LPA: β =-0.48 kg, 95% CI: -1.23, 0.27; sleep: β = 0.10 kg, 95% CI: -0.37, 0.57). This study provides the first normative reference values for handgrip strength from Northern Europe. These values offer a useful reference for screening and contextual interpretation of muscular strength in preschool children. Show less

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR- Show less

Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates. Show less

The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149). We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits. Show less