👤 Niina Pitkänen

Amyloid-β (Aβ) PET imaging is a core biomarker and is considered sufficient for the biological diagnosis of Alzheimer's disease (AD). However, it is typically reduced to a binary Aβ™/Aβ+ classification. In this study, we aimed to identify subgroups along the continuum of Aβ accumulation including subgroups within Aβ- and Aβ+. We used a total of 3,110 of Aβ PET scans from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) datasets to develop Show less

Therapeutic plasma exchange (TPE), with solvent/detergent (S/D)-treated plasma as replacement fluid, is an extracorporeal blood purification technique with major impact on both coagulation and lipids. Our previous in vitro study showed that S/D-plasma enhances thrombin generation by lowering intact protein S (PS) levels. To evaluate the impact of altered lipid balance on coagulation phenotype during heparin-anticoagulated TPE with S/D-plasma, and to investigate whether the lowered intact PS levels with concomitant procoagulant phenotype, are recapitulated in vivo. Coagulation biomarkers, thrombin generation with Calibrated Automated Thrombogram (CAT), and lipid levels were measured before and after the consecutive 1st, 3rd and 5th episodes of TPE performed to six patients with Guillain-Barré syndrome or myasthenia gravis. The effects of in vitro dilution of S/D-plasma on thrombin generation were explored with CAT to mimic TPE. Patients did not have coagulation disorders, except elevated FVIII. Intact PS, lipoproteins, especially LDL, Apolipoprotein CIII (ApoC3) and ApoB/ApoA1 ratio declined (p < 0.05). In contrast, VLDL and triglyceride levels stayed intact. CAT lag time shortened (p < 0.05). In vitro dilution of S/D plasma with co-transfused Ringer's lactate and 4% albumin partially reduced its procoagulant phenotype in CAT, which is mainly seen as peak thrombin, and modestly shortened lag time. After the five settings of TPE using S/D-plasma in vivo, which associated with heparinization and reduced coagulation factor activities, our observations of declining natural anticoagulant intact PS and apolipoproteins refer to rebalance of the hemostatic and lipid profiles. Show less

ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; Our results identified genetic variants in the Show less

Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2-18 years old) and 15 599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1888 cases and 4689 controls from seven cohorts of European and North/South American ancestry. In addition to observing 18 previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene, METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci. Show less

To evaluate the presence of serum protein biomarkers associated with the early phases of formation of carotid atherosclerotic plaques, label-free quantitative proteomics analyses were made for serum samples collected as part of The Cardiovascular Risk in Young Finns Study. Samples from subjects who had an asymptomatic carotid artery plaque detected by ultrasound examination (N = 43, Age = 30-45 years) were compared with plaque free controls (N = 43) (matched for age, sex, body weight and systolic blood pressure). Seven proteins (p < 0.05) that have been previously linked with atherosclerotic phenotypes were differentially abundant. Fibulin 1 proteoform C (FBLN1C), Beta-ala-his-dipeptidase (CNDP1), Cadherin-13 (CDH13), Gelsolin (GSN) and 72 kDa type IV collagenase (MMP2) were less abundant in cases, whereas Apolipoproteins C-III (APOC3) and apolipoprotein E (APOE) were more abundant. Using machine learning analysis, a biomarker panel of FBLN1C, APOE and CDH13 was identified, which classified cases from controls with an area under receiver-operating characteristic curve (AUROC) value of 0.79. Furthermore, using selected reaction monitoring mass spectrometry (SRM-MS) the decreased abundance of FBLN1C was verified. In relation to previous associations of FBLN1C with atherosclerotic lesions, the observation could reflect its involvement in the initiation of the plaque formation, or represent a particular risk phenotype. Show less

Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. Show less

A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex- and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value < 5 × 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 × 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index. Show less

Phosphomannose isomerase (PMI40) catalyzes the conversion between fructose 6-phosphate and mannose 6-phosphate and thus connects glycolysis, i.e. energy production and GDP-mannose biosynthesis or cell wall synthesis in Saccharomyces cerevisiae. After PMI40 deletion (pmi(-)) the cells were viable only if fed with extracellular mannose and glucose. In an attempt to force the GDP-mannose synthesis in the pmi(-) strain by increasing the extracellular mannose concentrations, the cells showed significantly reduced growth rates without any alterations in the intracellular GDP-mannose levels. To reveal the mechanisms resulting in reduced growth rates, we measured genome-wide gene expression levels, several metabolite concentrations, and selected in vitro enzyme activities in central metabolic pathways. The increasing of the initial mannose concentration led to an increase in the mannose 6-phosphate concentration, which inhibited the activity of the second enzyme in glycolysis, i.e. phosphoglucose isomerase converting glucose 6-phosphate to fructose 6-phosphate. As a result of this limitation, the flux through glycolysis was decreased as was the median expression of the genes involved in glycolysis. The expression levels of RAP1, a transcription factor involved in the regulation of the mRNA levels of several enzymes in glycolysis, as well as those of cell cycle regulators CDC28 and CLN3, decreased concomitantly with the growth rates and expression of many genes encoding for enzymes in glycolysis. Show less