Browsing by Subject "Heritability"

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  • Noreikiene, Kristina; Kuparinen, Anna; Merilae, Juha (2017)
    Telomeres are highly conserved nucleoprotein structures which protect genome integrity. The length of telomeres is influenced by both genetic and environmental factors, but relatively little is known about how different hereditary and environmental factors interact in determining telomere length. We manipulated growth rates and timing of maturation by exposing full-sib nine-spined sticklebacks (Pungitius pungitius) to two different temperature treatments and quantified the effects of temperature treatments, sex, timing of maturation, growth rate and family (genetic influences) on telomere length. We did not find the overall effect of temperature treatment on the relative telomere length. However, we found that variation in telomere length was related to timing of maturation in a sex- and temperature-dependent manner. Telomere length was negatively related to age at maturation in elevated temperature and early maturing males and females differed in telomere length. Variation in growth rate did not explain any variation in telomere length. The broad sense heritability (h(2)) of telomere length was estimated at h(2) = 0.31 - 0.47, suggesting predominance of environmental over genetic determinants of telomere length variability. This study provides the first evidence that age at maturation together with factors associated with it are influencing telomere length in an ectotherm. Future studies are encouraged to identify the extent to which these results can be replicated in other ectotherms.
  • Mai, The Tien; Turner, Paul; Corander, Jukka (2021)
    Background Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature. Results In this paper, we propose a generic strategy for heritability inference, termed as "boosting heritability", by combining the advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads in general to a stable and accurate estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy. Conclusions Boosting is shown to offer a reliable and practically useful tool for inference about heritability.
  • Mai, The T; Turner, Paul; Corander, Jukka (BioMed Central, 2021)
    Abstract Background Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature. Results In this paper, we propose a generic strategy for heritability inference, termed as “boosting heritability”, by combining the advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads in general to a stable and accurate estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy. Conclusions Boosting is shown to offer a reliable and practically useful tool for inference about heritability.
  • Ottensmann, Linda (Helsingin yliopisto, 2020)
    It is challenging to identify causal genes and pathways explaining the associations with diseases and traits found by genome-wide association studies (GWASs). To solve this problem, a variety of methods that prioritize genes based on the variants identified by GWASs have been developed. In this thesis, the methods Data-driven Expression Prioritized Integration for Complex Traits (DEPICT) and Multi-marker Analysis of GenoMic Annotation (MAGMA) are used to prioritize causal genes based on the most recently published publicly available schizophrenia GWAS summary statistics. The two methods are compared using the Benchmarker framework, which allows an unbiased comparison of gene prioritization methods. The study has four aims. Firstly, to explain what are the differences between the gene prioritization methods DEPICT and MAGMA and how the two methods work. Secondly, to explain how the Benchmarker framework can be used to compare gene prioritization methods in an unbiased way. Thirdly, to compare the performance of DEPICT and MAGMA in prioritizing genes based on the latest schizophrenia summary statistics from 2018 using the Benchmarker framework. Lastly, to compare the performance of DEPICT and MAGMA on a schizophrenia GWAS with a smaller sample size by using Benchmarker. Firstly, the published results of the Benchmarker analyses using schizophrenia GWAS from 2014 were replicated to make sure that the framework is run correctly. The results were very similar and both the original and the replicated results show that DEPICT and MAGMA do not perform significantly differently. Furthermore, they show that the intersection of genes prioritized by DEPICT and MAGMA outperforms the outersection, which is defined as genes prioritized by only one of these methods. Secondly, Benchmarker was used to compare the performance of DEPICT and MAGMA on prioritizing genes using the schizophrenia GWAS from 2018. The results of the Benchmarker analyses suggest that DEPICT and MAGMA perform similarly with the GWAS from 2018 compared to the GWAS from 2014. Furthermore, an earlier schizophrenia GWAS from 2011 was used to check if the performance of DEPICT and MAGMA differs when a GWAS with lower statistical power is used. The results of the Benchmarker analyses make clear that MAGMA performs better than DEPICT in prioritizing genes using this smaller data set. Furthermore, for the schizophrenia GWAS from 2011 the outersection of genes prioritized by DEPICT and MAGMA outperforms the intersection. To conclude, the Benchmarker framework is a useful tool for comparing gene prioritization methods in an unbiased way. For the most recently published schizophrenia GWAS from 2018 there is no significant difference between the performance of DEPICT and MAGMA in prioritizing genes according to Benchmarker. For the smaller schizophrenia GWAS from 2011, however, MAGMA outperformed DEPICT.
  • Lappalainen, Anu Katriina; Mäki, Katariina; Laitinen-Vapaavuori, Outi (2015)
    Background: Intervertebral disc disease (IDD) is a hereditary condition particularly common in Dachshunds. The breed is predisposed to early intervertebral disc degeneration and intervertebral disc calcification (IDC). When calcified, these severely degenerated discs are visible in spinal radiographs. Since the number of calcified discs (NCD) is associated with IDD, spinal radiography can be utilized in screening programmes in attempts to diminish the incidence of IDD in Dachshunds. Our aims were to estimate the heritability and genetic trend of NCD in Dachshunds in Finland and to explore the effect of age at the time of radiographic screening. Since the NCD has a highly skewed distribution, a log-transformed NCD (lnNCD) was also used as an analysed trait. The variance components for both traits were estimated, using the restricted maximum likelihood method. The fixed effects of breed variant, sex, as well as year of screening and the random effects of litter and animal were included in the model. The genetic trends in the NCD and lnNCD were assessed from the estimated breeding values (EBVs) of individual dogs by comparing the mean EBV of dogs born in different years. The breeding values were estimated, using the best linear unbiased prediction animal model. The pedigree in the genetic analyses included a total of 9027 dogs, of which 1567 showed results for NCDs. Results: The heritability estimates of the NCD and lnNCD in Dachshunds were high (0.53 and 0.45, respectively). Small genetic improvements were seen as the mean EBVs increased from 100 to 104 and 105 over a 15-year period. The gain in the entire Dachshund population in Finland may differ from that observed, since less than 10 % of the Dachshunds registered have a screening result for NCD. Age at the time of the screening did not significantly affect the NCD or lnNCD. Conclusions: We recommend systematic radiographic screening for IDC in Dachshunds and adopting EBVs as a tool for selecting breeding dogs. Age at the time of the radiographic screening may not be as important as previously suggested.
  • Kavlak, Alper Tuna; Stranden, Erling; Lidauer, M. H.; Uimari, Pekka (2021)
    Pigs are housed in groups during the test period. Social effects between penmates may affect average daily gain (ADG), backfat thickness (BF), feed conversion rate (FCR), and the feeding behaviour traits of pigs sharing the same pen. The aim of our study was to estimate the genetic parameters of feeding behaviour and production traits with statisticalmodels that include social genetic effects (SGEs). The data contained 3075 Finnish Yorkshire, 3351 Finnish Landrace, and 968 F1-crossbred pigs. Feeding behaviour traits were measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent in feeding per visit (TPV), feed intake per visit (FPV), and feed intake rate (FR). The test period was divided into five periods of 20 days. The number of pigs per pen varied from 8 to 12. Two model approaches were tested, i.e. a fixed group size model and a variable group size model. For the fixed group size model, eight random pigs per pen were included in the analysis, while all pigs in a pen were included for the variable group size model. The linear mixed-effectsmodel included sex, breed, and herd*year*season as fixed effects and group (batch*pen), litter, the animal itself (direct genetic effect (DGE)), and penmates (SGEs) as random effects. For feeding behaviour traits, estimates of the total heritable variation (T-2 +/- SE) and classical heritability (h(2) +/- SE, values given in brackets) from the variable group size model (e.g. period 1) were 0.34 +/- 0.13 (0.30 +/- 0.04) for NVD, 0.41 +/- 0.10 (0.37 +/- 0.04) for TPD, 0.40 +/- 0.15 (0.14 +/- 0.03) for DFI, 0.53 +/- 0.15 (0.28 +/- 0.04) for TPV, 0.66 +/- 0.17 (0.28 +/- 0.04) for FPV, and 0.29 +/- 0.13 (0.22 +/- 0.03) for FR. The effect of social interaction was minimal for ADG (T-2 = 0.29 +/- 0.11 and h(2) = 0.29 +/- 0.04), BF (T-2 = 0.48 +/- 0.12 and h(2) = 0.38 +/- 0.07), and FCR (T-2 = 0.37 +/- 0.12 and h(2) = 0.29 +/- 0.04) using the variable group size model. In conclusion, the results indicate that social interactions have a considerable indirect genetic effect on the feeding behaviour and FCR of pigs but not on ADG and BF. (C) 2020 The Authors. Published by Elsevier Inc. on behalf of The Animal Consortium.
  • CHD Exome Consortium; Consortium Genetics Smoking; EPIC-CVD Consortium; Understanding Soc Sci Grp; Brazel, David M.; Jiang, Yu; Hughey, Jordan M.; Loukola, Anu; Qaiser, Beenish; Kaprio, Jaakko; Kontto, Jukka; Perola, Markus; Dunning, Alison M. (2019)
    BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.
  • Huovinen, Joel; Kastinen, Sami; Komulainen, Simo; Oinas, Minna; Avellan, Cecilia; Frantzen, Janek; Rinne, Jaakko; Ronkainen, Antti; Kauppinen, Mikko; Lonnrot, Kimmo; Perola, Markus; Pyykko, Okka T.; Koivisto, Anne M.; Remes, Anne M.; Soininen, Hilkka; Hiltunen, Mikko; Helisalmi, Seppo; Kurki, Mitja; Jaaskelainen, Juha E.; Leinonen, Ville (2016)
    Idiopathic normal pressure hydrocephalus (iNPH) is a late-onset surgically alleviated, progressive disease. We characterize a potential familial subgroup of iNPH in a nation-wide Finnish cohort of 375 shunt-operated iNPH-patients. The patients were questionnaired and phone-interviewed, whether they have relatives with either diagnosed iNPH or disease-related symptomatology. Then pedigrees of all families with more than one iNPH-case were drawn. Eighteen patients (4.8%) from 12 separate pedigrees had at least one shunt-operated relative whereas 42 patients (11%) had relatives with two or more triad symptoms. According to multivariate logistic regression analysis, familial iNPH-patients had up to 3-fold risk of clinical dementia compared to sporadic iNPH patients. This risk was independent from diagnosed Alzheimer's disease and APOE epsilon 4 genotype. This study describes a familial entity of iNPH offering a novel approach to discover the potential genetic characteristics of iNPH. Discovered pedigrees offer an intriguing opportunity to conduct longitudinal studies targeting potential preclinical signs of iNPH. (C) 2016 Elsevier B.V. All rights reserved.
  • Hemminki, Kari; Hemminki, Otto; Koskinen, Anni I. M.; Försti, Asta; Sundquist, Kristina; Sundquist, Jan; Li, Xinjun (2018)
    Background: According to the literature the three stone diseases, sialolithiasis (SL), urolithiasis (UL) and cholelithiasis (CL) share comorbidities. We assess familial and spouse risks between these stone disease and compare them to familial risks for concordant (same) stone disease. Methods: Study population including familiar relationships was obtained from the Swedish Multigeneration Register and stone disease patients were identified from nation-wide medical records. Standardized incidence ratios (SIRs) were calculated for 0-83 year old offspring when their first-degree relatives were diagnosed with stone disease and the rates were compared to individuals without a family history of stone disease. Numbers of offspring with SL were 7906, for UL they were 170,757 and for CL they were 204,369. Results: SIRs for concordant familial risks were 2.06 for SL, 1.94 for UL and 1.82 for CL. SIRs for SL and UL were slightly higher for women than for men. Familial risks between stone diseases were modest. The highest risk of 1.17 was for UL when family members were diagnosed with CL, or vice versa. The SIR for UL was 1.15 when family members were diagnosed with SL. Familial risks among spouses were increased only for UL-CL pairs (1.10). Conclusions: Familial risks for concordant SL were 2.06 and marginally lower for the other diseases. Familial risks between stone diseases were low but higher than risks between spouses. The data show that familial clustering is unique to each individual stone disease which would imply distinct disease mechanisms. The results cast doubt on the reported comorbidities between these diseases.
  • Hemminki, Kari; Hemminki, Otto; Koskinen, Anni I M; Försti, Asta; Sundquist, Kristina; Sundquist, Jan; Li, Xinjun (BioMed Central, 2018)
    Abstract Background According to the literature the three stone diseases, sialolithiasis (SL), urolithiasis (UL) and cholelithiasis (CL) share comorbidities. We assess familial and spouse risks between these stone disease and compare them to familial risks for concordant (same) stone disease. Methods Study population including familiar relationships was obtained from the Swedish Multigeneration Register and stone disease patients were identified from nation-wide medical records. Standardized incidence ratios (SIRs) were calculated for 0–83 year old offspring when their first-degree relatives were diagnosed with stone disease and the rates were compared to individuals without a family history of stone disease. Numbers of offspring with SL were 7906, for UL they were 170,757 and for CL they were 204,369. Results SIRs for concordant familial risks were 2.06 for SL, 1.94 for UL and 1.82 for CL. SIRs for SL and UL were slightly higher for women than for men. Familial risks between stone diseases were modest. The highest risk of 1.17 was for UL when family members were diagnosed with CL, or vice versa. The SIR for UL was 1.15 when family members were diagnosed with SL. Familial risks among spouses were increased only for UL-CL pairs (1.10). Conclusions Familial risks for concordant SL were 2.06 and marginally lower for the other diseases. Familial risks between stone diseases were low but higher than risks between spouses. The data show that familial clustering is unique to each individual stone disease which would imply distinct disease mechanisms. The results cast doubt on the reported comorbidities between these diseases.
  • Wang, Lijie; Mohammadnejad, Afsaneh; Li, Weilong; Lund, Jesper; Li, Shuxia; Clemmensen, Signe; Timofeeva, Maria; Soerensen, Mette; Mengel-From, Jonas; Christensen, Kaare; Hjelmborg, Jacob; Tan, Qihua (BioMed Central, 2021)
    Abstract Background Epigenetic inactivation of O6-methylguanine DNA-methyltransferase (MGMT) is associated with increased sensitivity to alkylating chemotherapeutic agents in glioblastoma patients. The genetic background underlying MGMT gene methylation may explain individual differences in treatment response and provide a clue to a personalized treatment strategy. Making use of the longitudinal twin design, we aimed, for the first time, to estimate the genetic contributions to MGMT methylation in a Danish twin cohort. Methods DNA-methylation from whole blood (18 monozygotic (MZ) and 25 dizygotic (DZ) twin pairs) repeated 10 years apart from the Longitudinal Study of Aging Danish Twins (LSADT) were used to search for genetic and environmental contributions to DNA-methylation at 170 CpG sites of across the MGMT gene. Both univariate and bivariate twin models were applied. The intraclass correlations, performed on cross-sectional data (246 MZ twin pairs) from an independent study population, the Middle-Aged Danish Twins (MADT), were used to assess the genetic influence at each CpG site of MGMT for replication. Results Univariate twin model revealed twelve CpG sites showing significantly high heritability at intake (wave 1, h2 > 0.43), and seven CpG sites with significant heritability estimates at end of follow-up (wave 2, h2 > 0.5). There were six significant CpG sites, located at the gene body region, that overlapped among the two waves (h2 > 0.5), of which five remained significant in the bivariate twin model, which was applied to both waves. Within MZ pair correlation in these six CpGs from MADT demarks top level of genetic influence. There were 11 CpGs constantly have substantial common environmental component over the 10 years. Conclusions We have identified 6 CpG sites linked to the MGMT gene with strong and persistent genetic control based on their DNA methylation levels. The genetic basis of MGMT gene methylation could help to explain individual differences in glioblastoma treatment response and most importantly, provide references for mapping the methylation Quantitative Trait Loci (meQTL) underlying the genetic regulation.
  • Dubois, Lise; Diasparra, Maikol; Bedard, Brigitte; Kaprio, Jaakko; Fontaine-Bisson, Benedicte; Tremblay, Richard; Boivin, Michel; Perusse, Daniel (2013)
  • Mehtiö, Terhi; Mäntysaari, Päivi; Kokkonen, Tuomo; Kajava, Sari; Prestløkken, Egil; Kidane, Alemayehu; Wallén, Sini; Nyholm, Laura; Negussie, Enyew; Mäntysaari, Esa A.; Lidauer, Martin H. (2019)
    Digestibility traits included in this study were dry matter digestibility (DMD, g/kg), which was calculated based on the indigestible neutral detergent fibre (iNDF, g/kg of dry matter) content in faeces (iNDFf) and in diet (iNDFd), and iNDFf predicted directly from faecal samples by near infrared reflectance spectroscopy (NIRS). The data set was collected at three research herds in Finland and one in Norway including in total 931 records from 328 lactating Nordic Red Cattle and Holstein cows. Observations were associated with different accuracy, due to the differences in sampling protocols used for collecting faecal samples. Heritability estimates varied between different sampling protocols and ranged from 0.14 ± 0.06 to 0.51 ± 0.24 for DMD and from 0.13 ± 0.05 to 0.48 ± 0.18 for iNDFf. Estimated genetic standard deviations were 10.5 g/kg and 6.2 g/kg dry matter for DMD and iNDFf, respectively. Results of our study indicated that recording only the iNDF content in the faeces is sufficient to determine genetic variation in cows’ ability to digest feed. The coefficient of genetic variation for DMD was rather small (1.7%), but could be utilized if it is supported by a positive analysis of benefits over costs.
  • Lehtonen, Leevi (Helsingin yliopisto, 2021)
    Sex differences can be found in most human phenotypes, and they play an important role in human health and disease. Females and males have different sex chromosomes, which are known to cause sex differences, as are differences in the concentration of sex hormones such as testosterone, estradiol and progesterone. However, the role of the autosomes has remained more debated. The primary aim of this thesis is to assess the magnitude and relevance of human sex-specific genetic architecture in the autosomes. This is done by calculating sex-specific heritability estimates and genetic correlation estimates between females and males, as well as comparing these to sex differences on the phenotype level. Additionally, the heritability and genetic correlation estimates are compared between two populations, in order to assess the magnitude of sex differences compared to differences between populations. The analyses in this thesis are based on sex-stratified genome-wide association study (GWAS) data from 48 phenotypes in the UK Biobank (UKB), which contains genotype data from approximately 500 000 individuals as well as thousands of phenotype measurements. A replication of the analyses using three phenotypes was also made on data from the FinnGen project, with a dataset from approximately 175 000 individuals. The 48 phenotypes used in this study range from biomarkers such as serum testosterone and albumin levels to general traits such as height and blood pressure. The heritability and genetic correlation estimates were calculated using linkage disequilibrium score regression (LDSC). LDSC fits a linear regression model between test statistic values of GWAS variants and linkage disequilibrium (LD) scores calculated from a reference population. For most phenotypes, the heritability and genetic correlation results show little evidence of sex differences. Serum testosterone level and waist-to-hip ratio are exceptions to this, showing strong evidence of sex differences both on the genetic and the phenotype level. However, the overall correlation between phenotype level sex differences and sex differences in heritability or genetic correlation estimates is low. The replication in the FinnGen dataset for height, weight and body mass index (BMI), showed that for these traits the differences in heritability estimates and genetic correlations between the Finnish and UK populations are comparable or larger than the differences found between males and females.