👤 M Laakso

In the nationwide FinHCM Study including 306 Finnish patients with hypertrophic cardiomyopathy (HCM), we have previously identified two founder mutations in the alpha-tropomyosin (TPM1-D175N) and myosin-binding protein C (MYBPC3-Q1061X) genes, accounting for 18% of all cases. Objective. To screen additional mutations, previously identified in eastern Finnish cohorts with HCM, in the FinHCM Study population. Ten mutations in the beta-myosin heavy chain gene (MYH7), TPM1, and MYBPC3 were screened. MYH7-R1053Q was found in 17 of 306 patients (5.6%). No carriers of MYH7-R719W or N696S were found. A novel TPM1-D175G mutation was found in a single patient. MYBPC3 mutations were found in 14 patients: IVS5-2A-C in two, IVS14-13G-A in two, K811del in six, and A851insT in four patients. Altogether, a HCM-causing mutation was identified in 32 patients, accounting for 10.5% of all cases. In addition, two MYBPC3 variants R326Q and V896M with uncertain pathogenicity were found in eight and in 10 patients, respectively. Combining the present findings with our previous results, a causative mutation was identified in 28% of the FinHCM cohort. MYH7-R1053Q was the third most common mutation, and should be screened in all new cases of HCM in Finland. Show less

Low-grade inflammation in obesity is associated with accumulation of the macrophage-derived cytokine osteopontin (OPN) in adipose tissue and induction of local as well as systemic insulin resistance. Since glucose-dependent insulinotropic polypeptide (GIP) is a strong stimulator of adipogenesis and may play a role in the development of obesity, we explored whether GIP directly would stimulate OPN expression in adipose tissue and thereby induce insulin resistance. GIP stimulated OPN protein expression in a dose-dependent fashion in rat primary adipocytes. The level of OPN mRNA was higher in adipose tissue of obese individuals (0.13 ± 0.04 vs. 0.04 ± 0.01, P < 0.05) and correlated inversely with measures of insulin sensitivity (r = -0.24, P = 0.001). A common variant of the GIP receptor (GIPR) (rs10423928) gene was associated with a lower amount of the exon 9-containing isoform required for transmembrane activity. Carriers of the A allele with a reduced receptor function showed lower adipose tissue OPN mRNA levels and better insulin sensitivity. Together, these data suggest a role for GIP not only as an incretin hormone but also as a trigger of inflammation and insulin resistance in adipose tissue. Carriers of the GIPR rs10423928 A allele showed protective properties via reduced GIP effects. Identification of this unprecedented link between GIP and OPN in adipose tissue might open new avenues for therapeutic interventions. Show less

Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies. Show less

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits. Show less

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits. Show less

Hypertrophic cardiomyopathy (HCM) is predominantly caused by a large number of various mutations in the genes encoding sarcomeric proteins. However, two prevalent founder mutations for HCM in the alpha-tropomyosin (TPM1-D175N) and myosin-binding protein C (MYBPC3-Q1061X) genes have previously been identified in eastern Finland. To assess the prevalence of these founder mutations in a large population of patients with HCM from all over Finland. Patients and methods. We screened for two founder mutations (TPM1-D175N and MYBPC3-Q1061X) in 306 unrelated Finnish patients with HCM from the regions covering a population of ∼4,000,000. The TPM1-D175N mutation was found in 20 patients (6.5%) and the MYBPC3-Q1061X in 35 patients (11.4%). Altogether, the two mutations accounted for 17.9% of the HCM cases. In addition, 61 and 59 relatives of the probands were found to be carriers of TPM1-D175N and MYBPC3-Q1061X, respectively. The mutations showed regional clustering. TPM1-D175N was prevalent in central and western Finland, and MYBPC3-Q1061X in central and eastern Finland. The TPM1-D175N and MYBPC3-Q1061X mutations account for a substantial part of all HCM cases in the Finnish population, indicating that routine genetic screening of these mutations is warranted in Finnish patients with HCM. Show less

Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age(2), sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction  = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction  = 0.014 vs. n = 71,611, Pinteraction  = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction  = 0.003) and the SEC16B rs10913469 (Pinteraction  = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal. Show less

The incretin hormone GIP (glucose-dependent insulinotropic polypeptide) promotes pancreatic β-cell function by potentiating insulin secretion and β-cell proliferation. Recently, a combined analysis of several genome-wide association studies (Meta-analysis of Glucose and Insulin-Related Traits Consortium [MAGIC]) showed association to postprandial insulin at the GIP receptor (GIPR) locus. Here we explored mechanisms that could explain the protective effects of GIP on islet function. Associations of GIPR rs10423928 with metabolic and anthropometric phenotypes in both nondiabetic (N = 53,730) and type 2 diabetic individuals (N = 2,731) were explored by combining data from 11 studies. Insulin secretion was measured both in vivo in nondiabetic subjects and in vitro in islets from cadaver donors. Insulin secretion was also measured in response to exogenous GIP. The in vitro measurements included protein and gene expression as well as measurements of β-cell viability and proliferation. The A allele of GIPR rs10423928 was associated with impaired glucose- and GIP-stimulated insulin secretion and a decrease in BMI, lean body mass, and waist circumference. The decrease in BMI almost completely neutralized the effect of impaired insulin secretion on risk of type 2 diabetes. Expression of GIPR mRNA was decreased in human islets from carriers of the A allele or patients with type 2 diabetes. GIP stimulated osteopontin (OPN) mRNA and protein expression. OPN expression was lower in carriers of the A allele. Both GIP and OPN prevented cytokine-induced reduction in cell viability (apoptosis). In addition, OPN stimulated cell proliferation in insulin-secreting cells. These findings support β-cell proliferative and antiapoptotic roles for GIP in addition to its action as an incretin hormone. Identification of a link between GIP and OPN may shed new light on the role of GIP in preservation of functional β-cell mass in humans. Show less

We investigated the effects of 34 genetic risk variants for hyperglycemia/type 2 diabetes on lipoprotein subclasses and particle composition in a large population-based cohort. The study included 6,580 nondiabetic Finnish men from the population-based Metabolic Syndrome in Men (METSIM) study (aged 57 ± 7 years; BMI 26.8 ± 3.7 kg/m(2)). Genotyping of 34 single nucleotide polymorphism (SNPs) for hyperglycemia/type 2 diabetes was performed. Proton nuclear magnetic resonance spectroscopy was used to measure particle concentrations of 14 lipoprotein subclasses and their composition in native serum samples. The glucose-increasing allele of rs780094 in GCKR was significantly associated with low concentrations of VLDL particles (independently of their size) and small LDL and was nominally associated with low concentrations of intermediate-density lipoprotein, all LDL subclasses, and high concentrations of very large and large HDL particles. The glucose-increasing allele of rs174550 in FADS1 was significantly associated with high concentrations of very large and large HDL particles and nominally associated with low concentrations of all VLDL particles. SNPs rs10923931 in NOTCH2 and rs757210 in HNF1B genes showed nominal or significant associations with several lipoprotein traits. The genetic risk score of 34 SNPs was not associated with any of the lipoprotein subclasses. Four of the 34 risk loci for type 2 diabetes or hyperglycemia (GCKR, FADS1, NOTCH2, and HNF1B) were significantly associated with lipoprotein traits. A GCKR variant predominantly affected the concentration of VLDL, and the FADS1 variant affected very large and large HDL particles. Only a limited number of risk loci for hyperglycemia/type 2 diabetes significantly affect lipoprotein metabolism. Show less

Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis. Show less

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less

OBJECTIVE Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084). RESULTS The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 x 10(-71)). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction. CONCLUSIONS Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes. Show less

Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)). Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 x 10(-8)), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10(-15) for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia. Show less

We investigated the presence of left ventricular hypertrophy (LVH) and features of diastolic dysfunction in genotype-confirmed children from families with hypertrophic cardiomyopathy (HCM) and healthy control children. In subjects with HCM-causing mutations, LVH usually does not evolve until adolescence. Diastolic dysfunction has not been systematically evaluated in children carrying HCM-causing mutations. All children (aged 1.5-16.7 years) from 14 HCM families with identified disease-causing mutations (the Arg719Trp mutation in the beta-myosin heavy chain gene [MYH7], the Asp175Asn mutation in the alpha-tropomyosin gene [TPM1], the Gln1061X mutation in the myosin-binding protein C gene [MYBPC3], and the IVS5-2A-->C mutation in the MYBPC3 gene) and 53 matched control children were examined with electrocardiography and 2- and 3-dimensional echocardiography (2DE and 3DE). Natriuretic peptides were measured in children from HCM families and 67 control children. Of 53 children from HCM families, 27 (51%) had a disease-causing mutation (G+). G+ children had slightly thicker septum on 2DE compared with the control children (P = .004), but only 3 (11%) of 27 G+ children exceeded the 95th percentile values of the body surface area-adjusted maximal LV thickness of healthy children (the major echocardiographic criterion for HCM). However, prolonged isovolumetric relaxation time, increased left atrial volume on 3DE, or increased levels of NT-proANP, all features suggestive of diastolic dysfunction, were found in 14 (52%) of 27 G+ children. In children with HCM-causing mutations, signs of diastolic dysfunction are found in about half of the cases, as LVH is present only in small percentage of these children. Show less

Hypertrophic cardiomyopathy (HCM) is a genetically and clinically heterogeneous myocardial disease caused by mutations in genes encoding sarcomeric proteins. To assess the genetic background and phenotypic expression of HCM in eastern Finland, we screened 35 unrelated patients with HCM from the Kuopio University Hospital area for variants in 9 genes encoding sarcomeric proteins with the PCR-SSCP method. We herewith describe our previous findings in five sarcomeric genes and also report hitherto unpublished data on four additional sarcomeric genes. Mutations in the cardiac myosin-binding protein C gene (MYBPC3) were most frequent, accounting for 26% of cases. A novel mutation (Gln1061X) in this gene was the most common mutation, found in 6 of 35 families and accounting for 17% of all cases. Other novel mutations in MYBPC3 (IVS5-2A --> C, IVS14-13G --> A, and Ex25deltaLys) were found in one family each. A previously described alpha-tropomyosin (TPM1) mutation (Asp175Asn) was found in 11% of cases. Haplotype analysis suggested that the two most common variants (MYBPC3-Gln1061X and TPM1-Asp175Asn) were founder mutations. Only one mutation (Arg719Trp) in the beta-myosin heavy chain gene (MYH7) was found in one family, and no disease-causing mutations were found in the genes encoding alpha-actin, cardiac troponin I, T, C, or myosin essential and regulatory light chains. Altogether, the aforementioned 6 mutations found in MYBPC3, TPM1, and MYH7 accounted for 61% of familial and 40% of all HCM cases. The mutations were associated mostly with benign or intermediary phenotypes with only few HCM-related deaths. We conclude that the genetic profile of HCM in eastern Finland is unique, characterized by few founder mutations with benign or intermediary phenotypes. 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