👤 Annamari Lundqvist

Elevated lipoprotein(a) [Lp(a)] is an important genetic risk factor for cardiovascular diseases (CVDs). Because Lp(a)-lowering therapies are limited, prevention focuses on identifying individuals with elevated Lp(a) and optimizing other modifiable risk factors. We aimed to assess the distribution of Lp(a) levels in Finnish adults and examine its association with other CVD risk factors, as well as the awareness, treatment, and control of dyslipidemia. Data were derived from the Healthy Finland health examination survey conducted in 2023, comprising a nationally representative sample of 5,484 adults. Lp(a) levels were categorized using a cut-point at 125 nmol/L. Other CVD risk factors included were dyslipidemia, abnormal glucose metabolism, hypertension, and obesity. Analyses were weighted taking into account the sampling design and non-participation to provide nationally representative results. Mean Lp(a) levels were 41.7 nmol/L (95% CI 39.0-44.3) in men (M) and 41.9 nmol/L (39.7-44.1) in women (W). Elevated Lp(a) was observed in 11.0% of men and 10.4% of women. Dyslipidemia was more prevalent among individuals with elevated Lp(a) (M: 88.1% vs. 78.4% p = 0.003, W: 79.2% vs. 73.2% p = 0.030) but this association reversed after correcting cholesterol for Lp(a). No associations were found between Lp(a) and other cardiometabolic risk factors. Individuals with elevated Lp(a) had slightly lower unawareness (M: 42.3% vs. 47.5%, p = 0.180, W: 38.8% vs.48.4%, p = 0.042) and better treatment (M: 38.1% vs. 31.7%, p = 0.010, W: 29.2% vs. 24.7%, p = 0.090) of dyslipidemia than those with lower levels while no association was found between Lp(a) and dyslipidemia control (M: 81.4% vs. 84.1%, p = 0.520, W: 74.6% vs. 73.0%, p = 0.740). Approximately one in ten Finnish adults had elevated Lp(a), a lower prevalence than in many other European populations but still affecting a substantial share of the population. Elevated Lp(a) was associated with higher prevalence of dyslipidemia prior to Lp(a) correction, but not with other CVD risk factors, and these individuals also showed slightly greater awareness and treatment of dyslipidemia. These findings emphasize the need for comprehensive management of modifiable CVD risk factors to reduce the overall burden of CVDs. Show less

Obesity is characterized by chronic inflammation that may contribute to insulin resistance and promote type 2 diabetes. We have investigated whether inflammatory responses to glycemic and insulinemic variations are altered in obese individuals. Eight obese and eight lean individuals without diabetes had undergone hyperinsulinemic-euglycemic-hypoglycemic and hyperglycemic clamps in a previous study. Using Proximity Extension Assay, 92 inflammatory markers were analyzed from plasma samples at fasting, hyperinsulinemia-euglycemia, hypoglycemia and hyperglycemia. In all participants, hyperinsulinemia, hypoglycemia and hyperglycemia led to reductions of 11, 19 and 62 out of the 70 fully evaluable biomarkers, respectively. FGF-21 increased during both hypoglycemia and hyperglycemia while IL-6 and IL-10 increased during hypoglycemia. In obese vs lean participants, Oncostatin-M, Caspase-8 and 4E-BP1 were more markedly suppressed during hypoglycemia, whereas VEGF-A was more markedly suppressed during hyperglycemia. BMI correlated inversely with changes of PD-L1 and CD40 during hyperinsulinemia, Oncostatin-M, TNFSF14, FGF-21 and 4EBP-1 during hypoglycemia and CCL23, VEGF-A and CDCP1 during hyperglycemia (Rho ≤ -0.50). HbA1c correlated positively with changes of MCP-2 and IL-15-RA during hyperinsulinemia (Rho ≥ 0.51) and inversely with changes of CXCL1, MMP-1 and Axin-1 during hypoglycemia (Rho ≤ -0.55). M-value correlated positively with changes of IL-12B and VEGF-A during hyperglycemia (Rho ≥ 0.51). Results above were significant (p < 0.05). Overall, hyperinsulinemia, hypo- and hyperglycemia led to suppression of several inflammatory markers and this tended to be more marked in individuals with obesity, insulin resistance and dysglycemia. Thus, acute glycemic or insulinemic variations do not seem to potentiate possible inflammatory pathways in the development of insulin resistance and disturbed glucose metabolism. Show less

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53,949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10(-9), MIR2113; rs17522122, P=2.55 × 10(-8), AKAP6; rs10119, P=5.67 × 10(-9), APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10(-6)). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10(-17)). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C. Show less