Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods

Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30–45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidomegenotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research.Research Council of FinlandSocial Insurance Institution of FinlandCompetitive State Research Financing of Expert Responsibility area of Kuopio, Tampere and Turku University HospitalsJuho Vainio FoundationPaavo Nurmi FoundationFinnish Foundation for Cardiovascular ResearchFinnish Cultural Foundation Finnish IT center for scienceSigrid Juselius FoundationTampere Tuberculosis FoundationEmil Aaltonen FoundationYrjo Jahnsson FoundationSigne and Ane Gyllenberg FoundationDiabetes Research Foundation of Finnish Diabetes Association 322098 286284 134309 126925 121584 124282 255381 256474 283115 319060 320297 314389 338395 330809 104821 129378 117797 141071 INFRAIA-2016-1-730897Horizon 2020European Research Council (ERC) European Commission 349708Tampere University Hospital Supporting FoundationFinnish Society of Clinical ChemistrySpanish Government RTI2018-098983-B-100Laboratoriolaaketieteen Edistamissaatio~SrIda Montinin saatioKalle Kaiharin saatioAarne Koskelon saatioFaculty of Medicine and Health Technology, Tampere UniversityProject HPC-EUROPA3 X51001 50191928EC Research Innovation Action under H2020 Programme 75532

Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods

Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value \u3c 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research

Blackdrop pelin ohjelmointi

Tämä opinnäytetyö käsittelee pelisuunnittelua ja ohjelmointia. Työni on suppea pelisuunnitelma, josta selviää pelin perusidea, pelin ohjelmointitapa ja näihin liittyvä lyhyt kuvaus pelin keskeisistä ominaisuuksista. Opinnäytetyössäni keskityin pelin ohjelmointiin ja opettelin samalla uuden pelientekoon käytettävän ohjelmiston käytön. Työ toimii apuna oman peli-idean esittelemisessä ja sen konseptin jatkotyöstössä. Tavoitteena oli opetella uusi pelien koodaukseen soveltuvan ohjelmointi alustan käyttö ja tehdä sillä lyhyt pelisovellutus. Kielenä tässä työssä käytin C Sharp (C# versio 7.0) ohjelmointikieltä, jota pelien kehittämiseen tarkoitettu unity-ohjelmointiympäristö tukee. Työhön liittyvät kuvat piirrettiin verkkoselaimessa toimivalla Piskel ja Windows Paint ohjelmalla, ja pelin lopputausta on kuvakaapattu animaatiosta. Pelin käyttämät äänet äänitin Windows 10:n mikrofoniohjelmalla ja editoinut ne Twisted Wave Online verkkoselain editorilla, osan äänistä otin freesound.org sivustolta ja niiden alkuperäiset tekijät on asianmukaisesti listattu lähdeluettelossa. Ohjelmoinnin tein omalla Windows 10 pohjaisella tietokoneellani tai käyttämällä sitä TeamViewer etäyhteys ohjelman kautta. Blackdrop pelin keskeiset ominaisuudet ohjelmoin yllä kuvatulla menetelmällä neljässä eri ohjelmointikehitysvaiheessa ja kuhunkin niihin liittyvät käskysarjat ja niiden liittyminen toisiinsa pelin ohjaamisessa on kuvattu työn kuvissa yksityiskohtaisesti. Pelissä pelihahmo tippuu alaspäin ja pelaajan tehtävä on ohjata tätä hahmoa väistelemällä erilaisia esteitä ja vihollisia pelin loppuun asti. Mikäli pelaajahahmon pudotessa sen ns. elämäpisteet vähenevät vaarojen kohtaamisen myötä nollaan, se palautuu pelikentän alkuun ja jatkuu siitä eteenpäin uudestaan kohti maalia. Peliä pelataan näppäimistön ja hiiren avulla. Työn pohjalta voidaan samalla ohjelmointimenetelmällä jatkokehittää esim. kännyköihin tai muihin pelilaitteisin soveltuva Blackdrop peli tai vastaava lyhyt sovellus. Työ toimii apuna oman peli-idean prototyypin esittelemisessä ja konseptin jatkotyöstössä.This thesis handles game design and programming. My work is a slim game plan that defines the basic idea of the game, the way it is programmed and a short description of the key features of the game. My efforts were concentrated on programming the game and learning to use the new program for game design. This work serves as a tool in presenting my game idea and its concepts. The objective was to learn how to use a new programming platform and making a small game. The programming language chose for the work was C Sharp (C# version 7.0), which is supported by the unity environment. Images used in work were made using Piskel-browser app and Windows Paint programs, with the final background being a screenshot from an animation. Some game sounds were recorded using the Windows 10 default microphone application and edited using Twisted Wave Online browser editor, others were taken from freesound.org, with the authors adequately credited in list of sources. Programming was done on my Windows 10 desktop at home or using the TeamViewer remote connection program. The central components of the game were programmed as described above in four different parts and the important parts of the scripts used and their interconnections are shown in pictures in detail. In the Blackdrop game its characters fall down (drop) and the gamers’ task is to guide these game characters by avoiding different kind of obstacles and enemies until the end of the game. If the characters so called life point falls zero when they meets obstacles and enemies during fall, the game automatically returns to levels starting point by continues again towards target. The game is played by using a keyboard and a mouse. From this work game development can be continued to create versions for mobile and other platforms. This works serves as a tool for presenting a prototype of the game idea and for further work on the concep

The effect of apolipoprotein E polymorphism on serum metabolome:a population-based 10-year follow-up study

Abstract Apolipoprotein E (apoE) is the key regulator of plasma lipids, mediating altered functionalities in lipoprotein metabolism – affecting the risk of coronary artery (CAD) and Alzheimer’s diseases, as well as longevity. Searching pathways influenced by apoE prior to adverse manifestations, we utilized a metabolome dataset of 228 nuclear-magnetic-resonance-measured serum parameters with a 10-year follow-up from the population-based Young Finns Study cohort of 2,234 apoE-genotyped (rs7412, rs429358) adults, aged 24–39 at baseline. At the end of our follow-up, by limiting FDR-corrected p &lt; 0.05, regression analyses revealed 180/228 apoE-polymorphism-related associations with the studied metabolites, in all subjects – without indications of apoE x sex interactions. Across all measured apoE- and apoB-containing lipoproteins, ε4 allele had consistently atherogenic and ε2 protective effect on particle concentrations of free/esterified cholesterol, triglycerides, phospholipids and total lipids. As novel findings, ε4 associated with glycoprotein acetyls, LDL-diameter and isoleucine – all reported biomarkers of CAD-risk, inflammation, diabetes and total mortality. ApoE-subgroup differences persisted through our 10-year follow-up, although some variation of individual metabolite levels was noticed. In conclusion, apoE polymorphism associate with a complex metabolic change, including aberrations in multiple novel biomarkers related to elevated cardiometabolic and all-cause mortality risk, extending our understanding about the role of apoE in health and disease