👤 Jani Heikkinen

Cerebrospinal fluid amyloid beta 42, total tau, and phosphorylated tau 181 are well accepted markers of Alzheimer's disease. These biomarkers better reflect disease pathogenesis compared to clinical diagnosis. Here, we perform a genome wide association study meta-analysis including 18,948 individuals of European ancestry and identify 12 genome-wide significant loci across all three biomarkers, eight of them novel. We replicate the association of biomarkers with APOE, CR1, GMNC/CCDC50 and C16orf95/MAP1LC3B. Novel loci include BIN1 for amyloid beta and GNA12, MS4A6A, SLCO1A2 with both total tau and phosphorylated tau 181, as well as additional loci on chr. 8, near ANGPT1 and chr. 9 near SMARCA2. We also demonstrate that these variants have significant association with Alzheimer's disease risk, disease progression and/or brain amyloidosis. The associated genes are implicated in lipid metabolism independent of APOE, coupled with autophagy and brain volume regulation driven by total tau and phosphorylated tau 181 dysregulation. Show less

The Using genotype and clinical endpoint data from the FinnGen genomic research project, we conducted Kaplan–Meier survival analyses and Cox proportional hazards models to assess the ages of onset for AD, anxiety, and type 2 diabetes. The key findings were replicated in the UK Biobank datasets. Additionally, we assessed several metabolic and inflammatory plasma biomarkers in relation to In FinnGen, both the These findings indicate that protective The online version contains supplementary material available at 10.1186/s13195-026-01957-1. Show less

Large-scale genome-wide studies of chronic hydrocephalus have been lacking. We conducted a genome-wide association study (GWAS) in normal pressure hydrocephalus (NPH). We used a case-control study design implementing FinnGen data containing 473,691 Finns with genotypes and nationwide health records. Patients with NPH were selected based on We included 1,522 patients with NPH (mean age 72.2 years, 53% women) and 451,091 controls (mean age 60.5 years, 44% women). In the GWAS comparing patients with NPH with the controls, we identified 6 gene regions significantly ( We identified 6 loci significantly associated with NPH in the thus far largest GWAS in chronic hydrocephalus. The genes near the top loci have previously been associated with blood-brain barrier and blood-CSF barrier function and with increased lateral brain ventricle volume. The effect sizes and allele frequencies remained similar in NPH and iNPH cohorts, indicating the identified loci are risk determinants for iNPH and likely not explained by associations with other etiologies. However, the exact role of these loci is still unknown, warranting further studies. Show less

Genome-wide association studies have enabled identification of thousands of loci for hundreds of traits. Yet, for most human traits a substantial part of the estimated heritability is unexplained. This and recent advances in technology to produce high-dimensional data cost-effectively have led to method development beyond standard common variant analysis, including single-phenotype rare variant and multi-phenotype common variant analysis, with the latter increasing power for locus discovery and providing suggestions of pleiotropic effects. However, there are currently no optimal methods and tools for the combined analysis of rare variants and multiple phenotypes. We propose a user-friendly software tool MARV for Multi-phenotype Analysis of Rare Variants. The tool is based on a method that collapses rare variants within a genomic region and models the proportion of minor alleles in the rare variants on a linear combination of multiple phenotypes. MARV provides analyses of all phenotype combinations within one run and calculates the Bayesian Information Criterion to facilitate model selection. The running time increases with the size of the genetic data while the number of phenotypes to analyse has little effect both on running time and required memory. We illustrate the use of MARV with analysis of triglycerides (TG), fasting insulin (FI) and waist-to-hip ratio (WHR) in 4,721 individuals from the Northern Finland Birth Cohort 1966. The analysis suggests novel multi-phenotype effects for these metabolic traits at APOA5 and ZNF259, and at ZNF259 provides stronger support for association (P MARV is a computationally efficient, flexible and user-friendly software tool allowing rapid identification of rare variant effects on multiple phenotypes, thus paving the way for novel discoveries and insights into biology of complex traits. Show less

Hypertrophic cardiomyopathy (HCM) is a genetic disorder characterized by cardiac hypertrophy caused by mutations in genes encoding sarcomere proteins. This study screened all patients with HCM from the Kuopio University Hospital region in eastern Finland for variants in the cardiac myosin-binding protein C gene ( MYBPC3). All 35 exons of MYBPC3 were screened by the single-strand conformation polymorphism method in 37 unrelated patients with HCM. In MYBPC3 we identified seven novel (Gln1061X, IVS5-2A-->C, IVS14-13G-->A, Ex25DeltaLys, Pro147Leu, Ser236Gly, and Arg1138His) and two previously reported (Arg326Gln, Val896Met) variants, all of which are predicted to affect the structure of the encoded protein. Four of the nine variants, a nonsense mutation Gln1061X, a splice acceptor mutation (IVS5-2A-->C), a novel substitution in intron 14 (IVS14-13G-->A), and a novel 3-bp deletion in exon 25 (Ex25DeltaLys) were concluded to be disease-causing mutations because they cosegregated with the HCM phenotype or were absent in more than 200 normal chromosomes, or both. The mutation Gln1061X was found most frequently, being present in 6 families (23 subjects) while the other three mutations were found in single families each. Haplotype analysis indicated a likely founder effect among the families carrying the Gln1061X mutation. We found four novel mutations in MYBPC3, accounting for approx. 38% of familial and 24% of all cases of HCM. In our previous and unpublished studies no more frequent cause of HCM has been found in genetic analyses of other eight sarcomeric proteins. Consequently MYBPC3 is the predominant gene for HCM in eastern Finland. In addition, several amino acid substitutions in MYBPC3 suspected to be not associated with HCM were identified, indicating that some of the missense variants found in MYBPC3 are possibly not disease-causing mutations. Show less