Browsing by Subject "MISSING HERITABILITY"

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  • Hebbar, Prashantha; Abubaker, Jehad Ahmed; Abu-Farha, Mohamed; Tuomilehto, Jaakko; Al-Mulla, Fahd; Thanaraj, Thangavel Alphonse (2019)
    Despite dedicated nation-wide efforts to raise awareness against the harmful effects of fast-food consumption and sedentary lifestyle, the Arab population continues to struggle with an increased risk for metabolic disorders. Unlike the European population, the Arab population lacks well-established genetic risk determinants for metabolic disorders, and the transferability of established risk loci to this population has not been satisfactorily demonstrated. The most recent findings have identified over 240 genetic risk loci (with similar to 400 independent association signals) for type 2 diabetes, but thus far only 25 risk loci (ADAMTS9, ALX4, BCL11A, CDKAL1, CDKN2A/B, COL8A1, DUSP9, FTO, GCK, GNPDA2, HMG20A, HNF1A, HNF1B, HNF4A, IGF2BP2, JAZF1, KCNJ11 , KCNQ1, MC4R, PPAR gamma, SLC30A8, TCF7L2, TFAP2B, TP53INP1, and WFS1) have been replicated in Arab populations. To our knowledge, large-scale population- or family-based association studies are non-existent in this region. Recently, we conducted genome-wide association studies on Arab individuals from Kuwait to delineate the genetic determinants for quantitative traits associated with anthropometry, lipid profile, insulin resistance, and blood pressure levels. Although these studies led to the identification of novel recessive variants, they failed to reproduce the established loci. However, they provided insights into the genetic architecture of the population, the applicability of genetic models based on recessive mode of inheritance, the presence of genetic signatures of inbreeding due to the practice of consanguinity, and the pleiotropic effects of rare disorders on complex metabolic disorders. This perspective presents analysis strategies and study designs for identifying genetic risk variants associated with diabetes and related traits in Arab populations.
  • Kemppainen, Petri; Husby, Arild (2018)
    A fundamental assumption in quantitative genetics is that traits are controlled by many loci of small effect. Using genomic data, this assumption can be tested using chromosome partitioning analyses, where the proportion of genetic variance for a trait explained by each chromosome (h(c)(2)), is regressed on its size. However, as h(c)(2)-estimates are necessarily positive (censoring) and the variance increases with chromosome size (heteroscedasticity), two fundamental assumptions of ordinary least squares (OLS) regression are violated. Using simulated and empirical data we demonstrate that these violations lead to incorrect inference of genetic architecture. The degree of bias depends mainly on the number of chromosomes and their size distribution and is therefore specific to the species; using published data across many different species we estimate that not accounting for this effect overall resulted in 28% false positives. We introduce a new and computationally efficient resampling method that corrects for inflation caused by heteroscedasticity and censoring and that works under a large range of dataset sizes and genetic architectures in empirical datasets. Our new method substantially improves the robustness of inferences from chromosome partitioning analyses.
  • Day-Williams, Aaron G.; McLay, Kirsten; Drury, Eleanor; Edkins, Sarah; Coffey, Alison J.; Palotie, Aarno; Zeggini, Eleftheria (2011)
  • Chan, Yingleong; Holmen, Oddgeir L.; Dauber, Andrew; Vatten, Lars; Havulinna, Aki S.; Skorpen, Frank; Kvaloy, Kirsti; Silander, Kaisa; Nguyen, Thutrang T.; Willer, Cristen; Boehnke, Michael; Perola, Markus; Palotie, Aarno; Salomaa, Veikko; Hveem, Kristian; Frayling, Timothy M.; Hirschhorn, Joel N.; Weedon, Michael N. (2011)
  • Sieberts, Solveig K.; Zhu, Fan; Garcia-Garcia, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornes, Oriol; Guney, Emre; Li, Hongdong; Marin, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O.; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S. K.; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-ud-din, Muhammad; Azencott, Chloe-Agathe; Bellon, Victor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R.; Marttinen, Pekka; Pirinen, Matti; Saarela, Janna; Tang, Jing; Wennerberg, Krister; Rheumatoid Arth Challenge (2016)
    Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge ( An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
  • Prasad, Rashmi B.; Lessmark, Anna; Almgren, Peter; Kovacs, Gyorgyi; Hansson, Ola; Oskolkov, Nikolay; Vitai, Marta; Ladenvall, Claes; Kovacs, Peter; Fadista, Joao; Lachmann, Michael; Zhou, Yuedan; Sonestedt, Emily; Poon, Wenny; Wollheim, Claes B.; Orho-Melander, Marju; Stumvoll, Michael; Tuomi, Tiinamaija; Paeaebo, Svante; Koranyi, Laszlo; Groop, Leif (2016)
    Aims/hypothesis Genome-wide association studies (GWAS) have identified more than 65 genetic loci associated with risk of type 2 diabetes. However, the contribution of distorted parental transmission of alleles to risk of type 2 diabetes has been mostly unexplored. Our goal was therefore to search for parent-of-origin effects (POE) among type 2 diabetes loci in families. Methods Families from the Botnia study (n = 4,211, 1,083 families) were genotyped for 72 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes and assessed for POE on type 2 diabetes. The family-based Hungarian Transdanubian Biobank (HTB) (n = 1,463, > 135 families) was used to replicate SNPs showing POE. Association of type 2 diabetes loci within families was also tested. Results Three loci showed nominal POE, including the previously reported variants in KCNQ1, for type 2 diabetes in families from Botnia (rs2237895: p(POE) = 0.037), which can be considered positive controls. The strongest POE was seen for rs7578597 SNP in the THADA gene, showing excess transmission of the maternal risk allele T to diabetic offspring (Botnia: p(POE) = 0.01; HTB p(POE) = 0.045). These data are consistent with previous evidence of allelic imbalance for expression in islets, suggesting that the THADA gene can be imprinted in a POE-specific fashion. Five CpG sites, including those flanking rs7578597, showed differential methylation between diabetic and non-diabetic donor islets. Conclusions/interpretation Taken together, the data emphasise the need for genetic studies to consider from which parent an offspring has inherited a susceptibility allele.
  • FinnGen Project; Locke, Adam E.; Havulinna, Aki S.; Pirinen, Matti; Eriksson, Johan G.; Ala-Korpela, Mika; Järvelin, Marjo-Riitta; Männikkö, Minna; Laivuori, Hannele; Palotie, Aarno; Salomaa, Veikko; Laakso, Markku; Ripatti, Samuli (2019)
    Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.
  • Pervjakova, N.; Kukushkina, V.; Haller, T.; Kasela, S.; Joensuu, A.; Kristiansson, K.; Annilo, T.; Perola, M.; Salomaa, V.; Jousilahti, P.; Metspalu, A.; Magi, R. (2018)
    The aim of the study was to explore the parent-of-origin effects (POEs) on a range of human nuclear magnetic resonance metabolites. Materials & methods: We search for POEs in 14,815 unrelated individuals from Estonian and Finnish cohorts using POE method for the genotype data imputed with 1000 G reference panel and 82 nuclear magnetic resonance metabolites. Results: Meta-analysis revealed the evidence of POE for the variant rs1412727 in PTPRD gene for the metabolite: triglycerides in medium very low-density lipoprotein. No POEs were detected for genetic variants that were previously known to have main effect on circulating metabolites. Conclusion: We demonstrated possibility to detect POEs for human metabolites, but the POEs are weak, and therefore it is hard to detect those using currently available sample sizes.
  • Int Parkinson's Dis Genomics Cons; Guerreiro, Rita; Escott-Price, Valentina; Tienari, Pentti J.; Myllykangas, Liisa; Oinas, Minna (2019)
    Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.
  • Kaseva, Nina; Vääräsmaki, Marja; Matinolli, Hanna-Maria; Sipola, Marika; Tikanmäki, Marjaana; Kanerva, Noora; Heinonen, Kati; Lano, Aulikki; Wolke, Dieter; Andersson, Sture; Jarvelin, Marjo-Riitta; Räikkönen, Katri; Eriksson, Johan G.; Männistö, Satu; Kajantie, Eero (2020)
    Background/Objectives Maternal pre-pregnancy overweight/obesity and gestational diabetes (GDM) are associated with increased fat deposition in adult offspring. The purpose of this study was to identify if maternal pre-pregnancy overweight (body mass index (BMI) >= 25 kg/m(2)) or GDM are associated with dietary quality or intake in adult offspring. Subjects/Methods Participants (n = 882) from two longitudinal cohort studies (ESTER Maternal Pregnancy Disorders Study and the Arvo Ylppo Longitudinal Study) completed a validated food-frequency questionnaire at a mean age of 24.2 years (SD 1.3). Diet quality was evaluated by a Recommended Finnish Diet Index (RDI). The study sample included offspring of normoglycaemic mothers with pre-pregnancy overweight/obesity (ONO = 155), offspring of mothers with GDM regardless of BMI (OGDM = 190) and offspring of mothers with normal weight and no GDM (controls;n = 537). Results Among men, daily energy and macronutrient intakes were similar in ONO and controls. However, after adjusting for current offspring characteristics, including BMI, daily carbohydrate intake relative to total energy intake was higher in ONO-men [2.2 percentages of total energy intake (95% confidence interval 0.4, 4.0)]. In ONO-women, macronutrient intakes relative to total energy intake were similar with controls, while total daily energy intake seemed lower [-587.2 kJ/day (-1192.0, 4.4)]. After adjusting for confounders, this difference was attenuated. Adherence to a healthy diet, as measured by RDI, was similar in ONO and controls [mean difference: men 0.40 (-0.38, 1.18); women 0.25 (-0.50, 1.00)]. In OGDM vs. controls, total energy and macronutrient intakes were similar for both men and women. Also adherence to a healthy diet was similar [RDI: men 0.09 (-0.62, 0.80); women -0.17 (-0.93, 0.59)]. Conclusions Our study suggested higher daily carbohydrate intake in male offspring exposed to maternal pre-pregnancy overweight/obesity, compared with controls. Prenatal exposure to GDM was not associated with adult offspring dietary intakes.
  • Kujala, Urho M.; Palviainen, Teemu; Pesonen, Paula; Waller, Katja; Sillanpää, Elina; Niemelä, Maisa; Kangas, Maarit; Vähä-Ypyä, Henri; Sievänen, Harri; Korpelainen, Raija; Jämsä, Timo; Männikkö, Minna; Kaprio, Jaakko (2020)
    Purpose Polygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples. Methods We calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC;N= 759-11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966;N= 3263-4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC. Results The PRS accounted from 0.07% to 1.44% of the variation (R-2) in the self-reported and objectively measured PA volumes (Pvalue range = 0.023 to
  • Okser, Sebastian; Pahikkala, Tapio; Airola, Antti; Salakoski, Tapio; Ripatti, Samuli; Aittokallio, Tero (2014)
  • Artigas, Maria Soler; Wain, Louise V.; Miller, Suzanne; Kheirallah, Abdul Kader; Huffman, Jennifer E.; Ntalla, Ioanna; Shrine, Nick; Obeidat, Ma'en; Trochet, Holly; McArdle, Wendy L.; Alves, Alexessander Couto; Hui, Jennie; Zhao, Jing Hua; Joshi, Peter K.; Teumer, Alexander; Albrecht, Eva; Imboden, Medea; Rawal, Rajesh; Lopez, Lorna M.; Marten, Jonathan; Enroth, Stefan; Surakka, Ida; Polasek, Ozren; Lyytikainen, Leo-Pekka; Granell, Raquel; Hysi, Pirro G.; Flexeder, Claudia; Mahajan, Anubha; Beilby, John; Bosse, Yohan; Brandsma, Corry-Anke; Campbell, Harry; Gieger, Christian; Glaeser, Sven; Gonzalez, Juan R.; Grallert, Harald; Hammond, Chris J.; Harris, Sarah E.; Hartikainen, Anna-Liisa; Heliovaara, Markku; Henderson, John; Hocking, Lynne; Horikoshi, Momoko; Hutri-Kahonen, Nina; Ingelsson, Erik; Johansson, Asa; Kemp, John P.; Kolcic, Ivana; Kumar, Ashish; Ripatti, Samuli; UK BiLEVE (2015)
    Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P <5 x 10(-8)) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.
  • FinnGen Consortium; Guindo-Martinez, Marta; Amela, Ramon; Bonas-Guarch, Silvia; Rüeger, Sina; Kurki, Mitja; Torrents, David (2021)
    Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases. Most genome-wide association studies assume an additive model, exclude the X chromosome, and use one reference panel. Here, the authors implement a strategy including non-additive models and find that the number of loci for age-related traits increases as compared to the additive model alone.
  • van der Loos, Matthijs J. H. M.; Rietveld, Cornelius A.; Eklund, Niina; Koellinger, Philipp D.; Rivadeneira, Fernando; Abecasis, Goncalo R.; Ankra-Badu, Georgina A.; Baumeister, Sebastian E.; Benjamin, Daniel J.; Biffar, Reiner; Blankenberg, Stefan; Boomsma, Dorret I.; Cesarini, David; Cucca, Francesco; de Geus, Eco J. C.; Dedoussis, George; Deloukas, Panos; Dimitriou, Maria; Eiriksdottir, Guony; Eriksson, Johan; Gieger, Christian; Gudnason, Vilmundur; Hoehne, Birgit; Holle, Rolf; Hottenga, Jouke-Jan; Isaacs, Aaron; Jarvelin, Marjo-Riitta; Johannesson, Magnus; Kaakinen, Marika; Kahonen, Mika; Kanoni, Stavroula; Laaksonen, Maarit A.; Lahti, Jari; Launer, Lenore J.; Lehtimaki, Terho; Loitfelder, Marisa; Magnusson, Patrik K. E.; Naitza, Silvia; Oostra, Ben A.; Perola, Markus; Petrovic, Katja; Quaye, Lydia; Raitakari, Olli; Ripatti, Samuli; Scheet, Paul; Schlessinger, David; Schmidt, Carsten O.; Schmidt, Helena; Schmidt, Reinhold; Senft, Andrea; Smith, Albert V.; Spector, Timothy D.; Surakka, Ida; Svento, Rauli; Terracciano, Antonio; Tikkanen, Emmi; van Duijn, Cornelia M.; Viikari, Jorma; Voelzke, Henry; Wichmann, H. -Erich; Wild, Philipp S.; Willems, Sara M.; Willemsen, Gonneke; van Rooij, Frank J. A.; Groenen, Patrick J. F.; Uitterlinden, Andre G.; Hofman, Albert; Thurik, A. Roy (2013)
  • Abraham, Gad; Bhalala, Oneil G.; de Bakker, Paul I. W.; Ripatti, Samuli; Inouye, Michael (2014)