Raimo Pakkanen

Abstract Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10 −8 ), 10 of which associate with CVD risk including five new loci- COL5A1 , GLTPD2 , SPTLC3 , MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

The surface (S)-layer protein of Lactobacillus brevis was isolated, purified, and characterized. The S-layer protein is the major protein of the cell, with an apparent molecular mass of 46 kDa in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Immunogold electron microscopy with polyclonal antiserum against the isolated 46-kDa protein was used to confirm the surface location of this protein. N-terminal amino acid sequences of the intact 46-kDa protein and its tryptic peptides were determined. The gene of the S-layer protein was amplified from the genome of L. brevis by polymerase chain reaction with oligonucleotides, synthesized according to the N-terminal amino acid sequences, as primers. The polymerase chain reaction fragments containing the entire S-layer gene and its regulatory regions were sequenced. Nucleic acid sequence analysis revealed one open reading frame with a capacity to encode a protein of 48,159 Da. From the regulatory region of the gene, two subsequent promoters and a ribosome binding site, showing typical features of prokaryotic consensus sequences, were found. The coding region contained a characteristic gram-positive-type signal peptide of 30 amino acids. Removal of the signal peptide results in a polypeptide of 435 amino acids, which is in excellent agreement with the size of the S-layer protein determined by SDS-PAGE. The size and the 5' end analyses of the S-layer transcripts confirmed the monocistronic nature of the S-layer operon and the functionality of the two promoters found.

Importance: A genetic contribution to preeclampsia susceptibility has been established but is still incompletely understood. Objective: To disentangle the underlying genetic architecture of preeclampsia and preeclampsia or other maternal hypertension during pregnancy with a genome-wide association study (GWAS) of hypertensive disorders of pregnancy. Design, Setting, and Participants: This GWAS included meta-analyses in maternal preeclampsia and a combination phenotype encompassing maternal preeclampsia and preeclampsia or other maternal hypertensive disorders. Two overlapping phenotype groups were selected for examination, namely, preeclampsia and preeclampsia or other maternal hypertension during pregnancy. Data from the Finnish Genetics of Pre-eclampsia Consortium (FINNPEC, 1990-2011), Finnish FinnGen project (1964-2019), Estonian Biobank (1997-2019), and the previously published InterPregGen consortium GWAS were combined. Individuals with preeclampsia or other maternal hypertension during pregnancy and control individuals were selected from the cohorts based on relevant International Classification of Diseases codes. Data were analyzed from July 2020 to February 2023. Exposures: The association of a genome-wide set of genetic variants and clinical risk factors was analyzed for the 2 phenotypes. Results: A total of 16 743 women with prior preeclampsia and 15 200 with preeclampsia or other maternal hypertension during pregnancy were obtained from FINNPEC, FinnGen, Estonian Biobank, and the InterPregGen consortium study (respective mean [SD] ages at diagnosis: 30.3 [5.5], 28.7 [5.6], 29.7 [7.0], and 28 [not available] years). The analysis found 19 genome-wide significant associations, 13 of which were novel. Seven of the novel loci harbor genes previously associated with blood pressure traits (NPPA, NPR3, PLCE1, TNS2, FURIN, RGL3, and PREX1). In line with this, the 2 study phenotypes showed genetic correlation with blood pressure traits. In addition, novel risk loci were identified in the proximity of genes involved in the development of placenta (PGR, TRPC6, ACTN4, and PZP), remodeling of uterine spiral arteries (NPPA, NPPB, NPR3, and ACTN4), kidney function (PLCE1, TNS2, ACTN4, and TRPC6), and maintenance of proteostasis in pregnancy serum (PZP). Conclusions and Relevance: The findings indicate that genes related to blood pressure traits are associated with preeclampsia, but many of these genes have additional pleiotropic effects on cardiometabolic, endothelial, and placental function. Furthermore, several of the associated loci have no known connection with cardiovascular disease but instead harbor genes contributing to maintenance of successful pregnancy, with dysfunctions leading to preeclampsialike symptoms.

The purpose of this study was to examine the effects of bovine colostrum supplementation (Bioenervi) on serum insulin-like growth factor I (IGF-I), immunoglobulin G, hormone, and amino acid and saliva immunoglobulin A concentrations during a strength and speed training period. Nine male sprinters and jumpers underwent three randomized experimental training treatments of 8 days separated by 13 days. The only difference in the treatments was the drink of 125 ml consumed per day. Posttraining increases were noticed for serum IGF-I in the 25-ml Bioenervi treatment (125 ml contained 25 ml Bioenervi) and especially in the 125-ml Bioenervi treatment (125 ml contained 125 ml Bioenervi) compared with the placebo (normal milk whey) treatment (P < 0.05). The change in IGF-I concentration during the 8-day periods correlated positively with the change in insulin concentration during the same periods with 25-ml Bioenervi treatment (r = 0.68; P = 0.045) and with 125-ml Bioenervi treatment (r = 0.69; P = 0.038). Serum immunoglobulin G, hormone, and amino acid and saliva immunoglobulin A responses were similar during the three treatments. It appears that a bovine colostrum supplement (Bioenervi) may increase serum IGF-I concentration in athletes during strength and speed training.