Annemari Käräjämäki
A5054337559- Genetic Associations and Epidemiology
- Diabetes and associated disorders
- Diabetes Management and Research
- Nutrition, Genetics, and Disease
- Diabetes Treatment and Management
- Pancreatic function and diabetes
- Bioinformatics and Genomic Networks
- Liver Disease Diagnosis and Treatment
- Artificial Intelligence in Healthcare
- Extracellular vesicles in disease
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Genetic Mapping and Diversity in Plants and Animals
- Diet and metabolism studies
- Gut microbiota and health
- Cancer-related gene regulation
- Metabolism, Diabetes, and Cancer
- Dialysis and Renal Disease Management
- Epigenetics and DNA Methylation
- Aortic aneurysm repair treatments
- AI in cancer detection
- Genomics and Rare Diseases
- Diabetes Management and Education
- Kruppel-like factors research
- Renin-Angiotensin System Studies
- Machine Learning in Healthcare
Vaasa Central Hospital
2014-2023
Institute for Molecular Medicine Finland
2023
University of Helsinki
2023
Northern Ostrobothnia Hospital District
2023
University of Kara
2017
Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential provide insights into pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative phenotypes: principal analysis involved 5,717 T2D subjects, 3,345 DKD. Promising signals were evaluated up 26,827 subjects (12,710 DKD). A combined T1D+T2D GWAS was...
OBJECTIVE Latent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis one potential strategy to gain insight into appropriate classification this subtype. RESEARCH DESIGN AND METHODS We performed first genome-wide association study LADA case subjects European ancestry versus population control (n = 2,634 vs. 5,947) compared against 2,454 968)...
Five subgroups were described in European diabetes patients using a data driven machine learning approach on commonly measured variables. We aimed to test the applicability of this phenotyping Indian individuals with young-onset type 2 diabetes.
Urinary extracellular vesicles (uEV) are a largely unexplored source of kidney-derived mRNAs with potential to serve as liquid kidney biopsy. We assessed ∼200 uEV mRNA samples from clinical studies by genome-wide sequencing discover mechanisms and candidate biomarkers diabetic disease (DKD) in Type 1 diabetes (T1D) replication 2 diabetes. Sequencing reproducibly showed >10,000 similarity transcriptome. T1D DKD groups 13 upregulated genes prevalently expressed proximal tubules, correlated...
Identification of coding variant associations for complex diseases offers a direct route to biological insight, but is dependent on appropriate inference concerning the causal impact those variants disease risk. We aggregated data 81,412 type 2 diabetes (T2D) cases and 370,832 controls diverse ancestry, identifying 40 distinct association signals (at 38 loci) reaching significance ( p <2.2×10 −7 ). Of these, 16 represent novel mapping outside known genome-wide study (GWAS) signals. make...
Abstract Background Diabetes is presently classified into two main forms, type 1 (T1D) and 2 diabetes (T2D), but especially T2D highly heterogeneous. A refined classification could provide a powerful tool individualize treatment regimes identify individuals with increased risk of complications already at diagnosis. Methods We applied data-driven cluster analysis (k-means hierarchical clustering) in newly diagnosed diabetic patients (N=8,980) from the Swedish ANDIS (All New Diabetics Scania)...
Abstract Background Type 2 diabetes (T2D) is a multi-organ disease defined by hyperglycemia resulting from different mechanisms. Using clinical parameters measured at diagnosis (age, BMI, HbA1c, HOMA2-B, HOMA2-IR and GAD autoantibodies) adult patients with have been reproducibly clustered into five subtypes, that differed clinically respect to progression outcomes. 1 In this study we use genetic information investigate if these subtypes distinct underlying drivers. Methods Genome-wide...
Newly-defined subgroups of type 2 diabetes mellitus (T2DM) have been reported from real-world cohorts but not in detail randomised clinical trials (RCTs).T2DM participants, uncontrolled on different pre-study therapies (n = 12.738; 82 % Caucasian; 44 with duration > 10 years) 14 RCTs, were assigned to new according age at onset diabetes, HbA1c, BMI, and fasting C-peptide using the nearest centroid approach. Subgroup distribution, characteristics influencing factors analysed.In both, pooled...
Diabetic kidney disease is a growing health burden that lacks specific early non-invasive diagnostic procedures. To approach solution for this clinical need, we sequenced microRNAs of urinary extracellular vesicles and performed biomarker discovery by small RNA sequencing in type 1 diabetes cohort including males with without albuminuria. The results were replicated or qPCR two independent cohorts four previously published datasets 2 as well both sexes. Non-diabetic prostate cancer used...
Abstract Aim/Hypothesis Five subgroups were described in European diabetes patients using a data driven machine learning approach on commonly measured variables. We aimed to test the applicability of this phenotyping Indian young-onset type 2 patients. Methods applied derived centroids diagnosed before 45 years age from WellGen (n = 1612) cohort. also de novo k-means clustering cohort validate subgroups. then compared clinical and metabolic-endocrine characteristics complication rates...
Abstract Diabetic kidney disease (DKD) is a severe complication of type 1 diabetes (T1D), which lacks non-invasive early biomarkers. Although less explored, mRNAs in urinary extracellular vesicles (uEV) could reflect changes the transcriptome during DKD development. We performed genome-wide mRNA sequencing >100 uEV samples from two T1D cohorts with 24-hour and overnight urine collections. Our pipeline allowed reproducible detection >10,000 bearing overall similarity to transcriptome....