FUTURE PERSPECTIVES

The combination of genetic risk score to a currently used set of predictors

has been shown to improve the accuracy in prediction of type II diabetes.²⁷³ Genetic risk prediction has been long studied in cardiovascular disease,²⁷⁴ and more recently the genetic risk scores have been invited to the clinic.²⁷⁵ Another important implication is the advance in the pathophysiological knowledge of AKI.²⁷¹ In Study II, the replication of the results of a

hypothesis-ˆ”‡‡•–—†›Ž‡†–‘–Š‡ϐ‹†‹‰–Šƒ–ƒ’‘’–‘•‹•Ǧ”‡Žƒ–‡†‰‡‡•‹‰Š–Šƒ˜‡ƒ”‘Ž‡

in AKI development in critically ill patients in septic shock. Moreover, the …‘–”ƒ†‹…–‹‰ϐ‹†‹‰‹–—†›”‡‰ƒ”†‹‰–Š‡HMOX1-repeat allele-length underlines the distinct pathophysiological mechanisms between different AKI sub-phenotypes.

A far-fetched clinical implication is gene therapy where the defective or missing gene is replaced by a functional copy.²⁷¹ It is not in use for AKI, however experimental models exist. In a murine model of ischemia-reperfusion damage to the kidney, it was found that transfection of the BCL2 gene modulated necrotic and apoptotic pathways and thus reduced the damage.²⁷⁶

Importantly, a more practical clinical implication would be the use of genetic information in individually designing pharmacological treatment.²⁷¹ In pharmacogenetics, the variability of drug response is analyzed according to genotype. An example is the degradation of catecholamines, which is suggested to be affected by genotype. Genetic variants in PNMT and COMT have been studied in association with AKI,172,178,182,191 and these variants associate with elevated endogenous noradrenalin. In the critically ill, synthetic catecholamines such as noradrenalin are frequently used

–‘ •—’’‘”– ‘”‰ƒ ˆ—…–‹‘Ǥ Š‡ ‘™Ž‡†‰‡ ‘ˆ –Š‡ ‰‡‘–›’‡ ‹ϐŽ—‡…‹‰

catecholamine metabolism and possible desensitization might aid in the selection of other vasopressors to be used, such as angiotensin II.²⁷⁷

6.7 FUTURE PERSPECTIVES

In the future, a hypothesis-free genome-wide genetic association study in a large cohort of critically ill patients is warranted. However, as

•—‰‰‡•–‡†„›‡•’‡…‹ƒŽŽ›–Š‡ϐ‹†‹‰•‘ˆ–—†‹‡•Ȃǡ…ƒ”‡ˆ—Ž†‹•–‹…–‹‘

of the phenotype of interest is essential. It appears that the predisposing factors are different in the sub-phenotypes of septic and cardiac-surgery-associated AKI. Within an AKI sub-phenotype, a sample large enough to

ƒ…Š‹‡˜‡•—ˆϐ‹…‹‡–’‘™‡”–‘†‡–‡…–ƒƒ••‘…‹ƒ–‹‘ƒ›‡‡†–Š‡…‘„‹ƒ–‹‘

of data from several databases.

In the genetically isolated Finnish population, the multiple population

„‘––Ž‡‡…• Šƒ˜‡ ‹ϐŽ—‡…‡† –Š‡ ƒ–—”‡ ‘ˆ ‰‡‡–‹… ˜ƒ”‹ƒ…‡Ǥ ‡…ƒ—•‡ ‘ˆ

increased drift and reduced selective pressure, potentially deleterious variants may be enriched and present at higher frequencies.²⁷⁸ Finns have few rare variants (minor allele frequency less than 0.5%) and an abundance

of low-frequency variants (minor allele frequency 2 to 5 %) compared to other populations.²⁷⁸ These unique features may aid in the discovery of causal variants in association with complex traits,²⁷⁸ such as AKI.

A large national FinnGen research initiative aims to gather the genomic

•ƒ’Ž‡• ‘ˆ ͷͲͲԝͲͲͲ ‹• „› –Š‡ ›‡ƒ” ʹͲʹ͵ ȋŠ––’•ǣȀȀ™™™Ǥϐ‹‰‡Ǥϐ‹ȀȌǤ As a UK Biobank initiative, this project is anticipated to advance the understanding of genomic variation in relation to health and disease.

Using a hypothesis-free study design such as GWAS has many advantages. The main goal of GWAS is to advance the understanding of the pathophysiology of a given disease to advance prevention or treatment. Even if the association between a variant at a locus and a trait is not explanatory for the mechanism, novel technology has advanced this understanding.²⁷⁹ ϐ‹†‹‰• Šƒ˜‡ ”‡•—Ž–‡† ‹ †‡ϐ‹‹‰ –Š‡ ”‘Ž‡ ‘ˆ ‰‡‡• ‹ †‹•‡ƒ•‡ǡ predicting the risk for a trait, as well as in the study of population genetics.

However, certain conditions must be taken in to account in order to draw …‘…Ž—•‹‘•Ǥ‡˜‡”ƒŽ–Š‹‰•ƒ”‡…‘•‹†‡”‡†ˆ‘”•—ˆϐ‹…‹‡–’‘™‡”ǡ‹…Ž—†‹‰ǣ the experimental sample size; the genetic architecture linking effect size to allele frequency of a variant at a locus; the number of those variants affecting the studied trait; the heterogeneity of the studied trait; and the panel of variants used in the GWAS.²⁷⁹ Some challenges persist, such as new

‹†‡–‹ϐ‹‡†Ž‘…‹™‹–Š•ƒŽŽ‡”‡ˆˆ‡…–•‹œ‡•‘”™‹–Š˜‡”›Ž‘™ˆ”‡“—‡…‹‡•ǡƒ•–Š‡

sample sizes grow ever larger.²⁷⁹ GWAS is a tool that by utilizing robust methodology yields highly replicable results.²⁸⁰ As it is very cost effective, GWAS will remain as the main instrument for discovering variation in association to complex traits for the time being.^279,280 However, phenotype predictability with GWAS remains very low^280,281 and still larger studies

ƒ•™‡ŽŽƒ•‹’”‘˜‡†‡–Š‘†•ƒ”‡‡‡†‡†–‘ˆƒ…‹Ž‹–ƒ–‡‰‡‡–‹…’”‘ϐ‹Ž‹‰‘ˆ

individuals at risk.²⁸⁰

Š‡†‡ϐ‹‹–‹‘‘ˆǡ‹ƒŽŽ–Š‡•—„Ǧ’Š‡‘–›’‡•ǡ…—””‡–Ž›”‡Ž‹‡•—’‘

’Žƒ•ƒ…”‡ƒ–‹‹‡ƒ†—”‹‡‘—–’—–ǤŠ—•ǡ‹•†‡ϐ‹‡†„›Ž‘••‘ˆˆ—…–‹‘

and in fact indicating impairment rather than injury. Performing these tests causes a delay in discovery of AKI. There is a pressing need for more accurate diagnostic tools to better identify the phenotype of interest.

ƒ•‡†‘–Š‡ϐ‹†‹‰•‘ˆ–—†‹‡•Ȃǡ‹–ƒ’’‡ƒ”•–Šƒ––Š‡‰‡‡–‹…˜ƒ”‹ƒ–•

in SERPINA4 and SERPINA5 carry the most evidence of association with AKI. These two protective variants within apoptosis-related genes were successfully replicated in association with AKI in Study II. However, the functions of these variants are unknown. In the future, research is needed about the potential role these variants in AKI susceptibility.

In presenting association of a genetic variant with AKI there is an

6 Epigenetic regulation of gene expression is a mechanism that does

not change the nucleotide sequence but induces changes to a phenotype

„›Š‹•–‘‡‘†‹ϐ‹…ƒ–‹‘•ǡ‡–Š›Žƒ–‹‘ǡƒ†˜‹ƒ‘Ǧ…‘†‹‰•Ǥ²⁸² These changes, although partly heritable, are potentially reversible and affected by environmental factors. It is suggested that an overall increase in histone acetylation would protect from AKI and shift the kidney toward regeneration; however, the precise mechanisms remain unknown.²⁸²

Genetic research has provided an advanced instrument in gaining understanding of the pathogenesis of many clinical conditions, as well as the possibilities of precision medicine in providing more individualized approaches to treatment of disease. The ongoing research into genetic and

‡’‹‰‡‡–‹…’”‡†‹•’‘•‹–‹‘ˆ‘”‹•˜‹‰‘”‘—•Ǥ‹–Š™‡ŽŽǦ†‡ϐ‹‡†’Š‡‘–›’‡•

of critical-care syndromes, the study of genetic variation will reveal the

‹†‹˜‹†—ƒŽˆ‡ƒ–—”‡•–Šƒ–‹ϐŽ—‡…‡†‹•‡ƒ•‡‘•‡–ƒ†’”‘‰”‡••‹‘Ǥ‹–Š–Š‹•

information, more individualized care can be designed for patients with risk or established AKI, who are equally entitled to adequate intervention, regardless of their genotype.

7 CONCLUSIONS

1. Based on the systematic review of the literature no conclusive evidence exists about the genetic predisposition to AKI.

Studies with larger sample size and better standardized AKI

†‡ϐ‹‹–‹‘ ƒ”‡ ‡‡†‡† –‘ ‰ƒ‹ …‘…Ž—•‹˜‡ ‡˜‹†‡…‡ ‘ˆ ‰‡‡–‹…

predisposition to AKI.

2. The published genetic studies were heterogeneous and of inadequate quality.

3.

3.1. In critically ill adult patients with septic shock, the variants rs2093266 in the SERPINA4 and rs1955656 in the SERPINA5 were associated with the development of severe AKI, implying an apoptotic pathway in this phenotype of AKI.

3.2. In critically ill patients with sepsis, the short allele of promoter repeat polymorphism of HMOX1 was associated with development of severe AKI.

3.3. ‡•–‡† ‰‡‡–‹… ˜ƒ”‹ƒ–• ™‹–Š‹ ʹ͹ ‹ϐŽƒƒ–‘”› ‰‡‡•

did not associate with development of severe or all-stage AKI in critically ill patients. The variants did not associate with the outcome in subgroups of septic or cardiac surgery cohorts.

7, 8

8 ACKNOWLEDGEMENTS

This study was carried out at the Helsinki University Central Hospital, Department of Anesthesiology and Intensive Care Medicine in the years 2011 through 2019. The study was part of the national multicenter FINNAKI study that included patients in 17 Finnish ICUs. I want to express my deepest gratitude to all of the study participants and the entire FINNAKI Study Group, who made this thesis possible. I am very thankful for ϐ‹ƒ…‹ƒŽ•—’’‘”–ˆ”‘–Š‡‘•’‹–ƒŽ†‹•–”‹…–‘ˆ‡Ž•‹‹ǡ–Š‡ ‹‹•Š‘…‹‡–›

of Anesthesiologists, the Finnish Kidney Foundation, and the University of Helsinki.

I most sincerely thank the supervisors of this thesis, docent Mari Kaunisto and professor Ville Pettilä. They have provided me with insightful guidance and extremely achievable support throughout this project. Due to Ville’s productiveness, exceptional research skills, and substantial knowledge about AKI my thesis project has been very forward driven. I am extremely fortunate to have been supervised by Mari, who is a true expert in genetics of complex traits, as well as an inspiring mentor. Indeed, I got to learn from the best.

I want to express my deepest gratitude to docent Tarja Kunnas and docent Satu Mäkelä for reviewing this thesis. Their precise work, sensible observations, and supportive comments were extremely valuable. I am most grateful to professor Klaus Olkkola and docent Tarja Randell, who have welcomed me in the clinical training program in anesthesiology and encouraged my research work. Members of the monitoring group of the thesis, docent Marjo Avela and professor Juha Sinisalo, are gratefully acknowledged.

I owe a special thanks to information specialist Katri Larmo for assistance in performing literature searches, and to Dr Jennifer Rowland for ϐ‹”•–Ǧ…Žƒ••Žƒ‰—ƒ‰‡‡†‹–‹‰Ǥ•‘Ž‹…‹–—Šƒ‹‹–¡‡ˆ‘”ƒ†˜‹…‡‹‰”ƒ’Š‹…• drawing, as well as excellent layout and cover design of this thesis.

Without the hands-on advice from docent Suvi Vaara I would not have any results to share. Her data-management skills are extraordinary, and she is most hard-working and ingenious researcher, who I truly look up to.

I am grateful to Meri Poukkanen, MD, PhD, and Sara Nisula, MD, PhD, for their excellent work in the FINNAKI project.

—•––Šƒ†‘…‡–¡‹˜‹ƒ‹•–‘ƒ††‘…‡–ƒ–‹‘‡”ˆ‘”ϐŽ‡š‹„Ž‡

and innovative co-operation in cowriting. My heartfelt thanks go to the laboratory specialists Anu Yliperttula, Hanna-Maria Nieminen, and Essi Kaiharju for giving me the basic knowledge about DNA sample processing.

I am deeply thankful to research coordinators Sari Sutinen and Leena Pettilä for helping me out at all times. I want to thank Iris Renken, MD,

ˆ‘” •Šƒ”‹‰ ƒ ‘ˆϐ‹…‡ ƒ† ƒ …‘‘ ‹–‡”‡•–ǡ „—– ‘”‡ ‹’‘”–ƒ–Ž› ˆ‘”

asking such good questions. I am in gratitude to research secretary Taina Vuorenmaa, who has managed the practical aspects of research work.

I praise my good friends Nelli, Heli, Harriet, Eija, Hertta, and Pia, who have supported me throughout this project. At the face of all challenges and enormous life changes I have been allowed to be myself in your presence;

thank you! Most humbly I thank my mother and my in-laws for helping out without question. Because of your assistance I have been able to pursue

›•…‹‡–‹ϐ‹…ƒ„‹–‹‘•ƒŽ‘‰•‹†‡›ˆ‘—†‹‰ƒˆƒ‹Ž›Ǥ

Finally, I have the opportunity to thank my family. My dear Markus, I am certain no one else would have been as loving, and as tolerant towards my constant requests for time for “nakki”. You have bravely stood beside me and endorsed me in times of doubt. Beloved Niilo and Veera, thank you for bringing joy and purpose to life. I am most proud to be your mother.

Helsinki, October 2019

Laura M. Vilander

8, 9

9 REFERENCES

1. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int - Suppl.2:1-138; 2012.

2. Nisula S, Yang R, Kaukonen K-M, Vaara ST, Kuitunen A, Tenhunen J, Pettilä V, Korhonen A-M, FINNAKI Study Group. The Urine Protein NGAL Predicts Renal Replacement Therapy, but Not Acute Kidney Injury or 90-Day Mortality in Critically Ill Adult Patients. Anesth Analg. 119:95-102; 2014.

3. Nisula S, Yang R, Poukkanen M, Vaara ST, Kaukonen K-M, Tallgren M, Haapio M, Tenhunen J, Korhonen A-M, Pettilä V, FINNAKI Study Group. Predictive value of urine interleukin-18 in the evolution and outcome of acute kidney injury in critically ill adult patients.

Br J Anaesth. 114:460-468; 2015.

4. Zhang WR, Parikh CR. Biomarkers of Acute and Chronic Kidney Disease. Annu Rev Physiol. 81:309-333; 2019.

5. Kellum JA, Sileanu FE, Bihorac A, Hoste EAJ, Chawla LS. Recovery after Acute Kidney Injury. Am J Respir Crit Care Med. 195:784-791;

2017.

6. Ostermann M, Liu K. Pathophysiology of AKI. Best Pract Res Clin Anaesthesiol. 31:305-314; 2017.

7. Kellum JA, Prowle JR. Paradigms of acute kidney injury in the intensive care setting. Nat Rev Nephrol. 14(4):217-230; 2018.

8. Frayling TM. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev. 8:657-662; 2007.

9. Gormley P, Anttila V, Winsvold BS, Palta P, Esko T, Pers TH, Farh K-H, Cuenca-Leon E, Muona M, Furlotte NA, Kurth T, Ingason A, McMahon G, Ligthart L, Terwindt GM, Kallela M, Freilinger TM, Ran C, Gordon SG, Stam AH, Steinberg S, Borck G, Koiranen M, Quaye L, Adams HHH, Lehtimäki T, Sarin A-P, Wedenoja J, Hinds DA, Buring JE, Schürks M, Ridker PM, Hrafnsdottir MG, Stefansson H, Ring SM, Hottenga J-J, Penninx BWJH, Färkkilä M, Artto V, Kaunisto M, Vepsäläinen S, Malik R, Heath AC, Madden PAF, Martin NG, Montgomery GW, Kurki MI, Kals M, Mägi R, Pärn K, Hämäläinen E, Huang H, Byrnes AE, Franke L, Huang J, Stergiakouli E, Lee PH, Sandor C, Webber C, Cader Z, Muller-Myhsok B, Schreiber

S, Meitinger T, Eriksson JG, Salomaa V, Heikkilä K, Loehrer E, Uitterlinden AG, Hofman A, van Duijn CM, Cherkas L, Pedersen LM, Stubhaug A, Nielsen CS, Männikkö M, Mihailov E, Milani L, Göbel H, Esserlind A-L, Christensen AF, Hansen TF, Werge T, Kaprio J, Aromaa AJ, Raitakari O, Ikram MA, Spector T, Järvelin M-R, Metspalu A, Kubisch C, Strachan DP, Ferrari MD, Belin AC, Dichgans M, Wessman M, van den Maagdenberg AMJM, Zwart J-A, Boomsma DI, Smith GD, Stefansson K, Eriksson N, Daly MJ, Neale BM, Olesen J, Chasman DI, Nyholt DR, Palotie A. Meta-analysis of

͵͹ͷǡͲͲͲ‹†‹˜‹†—ƒŽ•‹†‡–‹ϐ‹‡•͵ͺ•—•…‡’–‹„‹Ž‹–›Ž‘…‹ˆ‘”‹‰”ƒ‹‡Ǥ Nat Genet. 48:856-866; 2016.

10. Kerr KF, Meisner A, Thiessen-Philbrook H, Coca SG, Parikh CR.

Developing risk prediction models for kidney injury and assessing incremental value for novel biomarkers. Clin J Am Soc Nephrol.

9:1488-1496; 2014.

11. Warren M. The approach to predictive medicine that is taking genomics research by storm. Nature. 562:181-183; 2018.

12. Susantitaphong P, Cruz DN, Cerda J, Abulfaraj M, Alqahtani F, Koulouridis I, Jaber BL, Acute Kidney Injury Advisory Group of the American Society of Nephrology. World incidence of AKI: a meta-analysis. Clin J Am Soc Nephrol. 8:1482-1493; 2013.

13. Mehta RL, Cerdá J, Burdmann EA, Tonelli M, García-García G, Jha V, Susantitaphong P, Rocco M, Vanholder R, Sever MS, Cruz D, Jaber B, Lameire NH, Lombardi R, Lewington A, Feehally J, Finkelstein F, Levin N, Pannu N, Thomas B, Aronoff-Spencer E, Remuzzi G.

International Society of Nephrology’s 0by25 initiative for acute kidney injury (zero preventable deaths by 2025): a human rights case for nephrology. Lancet. 385:2616-2643; 2015.

14. Nisula S, Kaukonen K-M, Vaara ST, Korhonen A-M, Poukkanen M, Karlsson S, Haapio M, Inkinen O, Parviainen I, Suojaranta-Ylinen R, Laurila J, Tenhunen J, Reinikainen M, Ala-Kokko T, Ruokonen E, Kuitunen A, Pettilä V, FINNAKI Study Group. Incidence, risk factors and 90-day mortality of patients with acute kidney injury in Finnish intensive care units: the FINNAKI study. Intensive Care Med. 39:420-428; 2013.

9 Andrade E, Webb S, Kellum JA. Epidemiology of acute kidney injury

in critically ill patients: the multinational AKI-EPI study. Intensive Care Med. 41:1411-1423; 2015.

16. Poukkanen M, Vaara ST, Pettilä V, Kaukonen K-M, Korhonen A-M, Hovilehto S, Inkinen O, Laru-Sompa R, Kaminski T, Reinikainen M, Lund V, Karlsson S, FINNAKI Study Group. Acute kidney injury in patients with severe sepsis in Finnish Intensive Care Units. Acta Anaesthesiol Scand. 57:863-872; 2013.

17. Human Genome Sequencing Consortium I. Finishing the euchromatic sequence of the human genome. Nature. 431:931-945; 2004.

18. Human Molecular Genetics. Strachan T, Read AP. Basic principles of nucleic acid structure and gene expression. Boca Raton, FL: Taylor

& Francis; 2019:3-40.

19. Human Molecular Genetics. Strachan T, Read AP. Fundamentals of cells and chromosomes. Boca Raton, FL: Taylor & Francis; 2019:41-68.

20. Crick F. Central Dogma of Molecular Biology. Nature. 227:561-563;

1970.

21. Williams MA, Carson R, Passmore P, Silvestri G, Craig D. Introduction to genetic epidemiology. Optom - J Am Optom Assoc. 82:83-91;

2011.

22. Human Molecular Genetics. Strachan T, Read AP. An overview of human genetic variation. Boca Raton, FL: Taylor & Francis;

2019:361-396.

23. Manolio TA, Brooks LD, Collins FS. A HapMap harvest of insights into the genetics of common disease. J Clin Invest. 118:1590-1605;

2008.

24. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 21:263-265; 2005.

25. den Dunnen JT, Dalgleish R, Maglott DR, Hart RK, Greenblatt MS, McGowan-Jordan J, Roux A-F, Smith T, Antonarakis SE, Taschner PEM. HGVS Recommendations for the Description of Sequence Variants: 2016 Update. Hum Mutat. 37:564-569; 2016.

26. Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, Maglott DR. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res.

42:D980-5; 2014.

27. Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, Billis K, Cummins C, Gall A, Girón CG, Gil L, Gordon L, Haggerty L, Haskell E, Hourlier T, Izuogu OG, Janacek SH, Juettemann T, To JK, Laird MR, Lavidas I, Liu Z, Loveland JE, Maurel T, McLaren W, Moore B, Mudge J, Murphy DN, Newman V, Nuhn M, Ogeh D, Ong CK, Parker A, Patricio M, Riat HS, Schuilenburg H, Sheppard D, Sparrow H, Taylor K, Thormann A, Vullo A, Walts B, Zadissa A, Frankish A, Hunt SE, Kostadima M, Langridge N, Martin FJ, Muffato M, Perry E,

—ˆϐ‹‡”ǡ–ƒ‹‡•ǡ”‡˜ƒ‹‘ǡ‡ǡ—‹‰Šƒ ǡƒ–‡•

A, Flicek P. Ensembl 2018. Nucleic Acids Res. 46:D754-D761; 2018.

28. Mattar R, de Campos Mazo DF, Carrilho FJ. Lactose intolerance:

diagnosis, genetic, and clinical factors. Clin Exp Gastroenterol.

5:113-121; 2012.

29. New Clinical Genetics 3. Read AP, Donnai D. What do mutations do?

Banbury, UK: Scion Publishing Ltd; 2015:145-176.

30. Human Molecular Genetics. Strachan T, Read AP. Patterns of inheritance. Boca Raton, FL: Taylor & Francis; 2019:137-157.

31. Yang J, Zeng J, Goddard ME, Wray NR, Visscher PM. Concepts, estimation and interpretation of SNP-based heritability. Nat Genet.

49:1304-1310; 2017.

32. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, Cho JH, Guttmacher AE, Kong A, Kruglyak L, Mardis E, Rotimi CN, Slatkin M, Valle D, Whittemore AS, Boehnke M, Clark AG, Eichler EE, Gibson G, Haines JL, Mackay TFC, Mccarroll SA, Visscher PM. Finding the missing heritability of complex diseases. Nature. 461:747-753;

2009.

33. Human Molecular Genetics. Strachan T, Read AP. Complex disease:

identifying susceptibility factors and understanding pathogenesis.

9 35. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt

DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 42:565-569; 2010.

36. Yang J, Manolio TA, Pasquale LR, Boerwinkle E, Caporaso N, Cunningham JM, de Andrade M, Feenstra B, Feingold E, Hayes MG, Hill WG, Landi MT, Alonso A, Lettre G, Lin P, Ling H, Lowe W, Mathias RA, Melbye M, Pugh E, Cornelis MC, Weir BS, Goddard ME, Visscher PM. Genome partitioning of genetic variation for complex traits using common SNPs. Nat Genet. 43:519-525; 2011.

37. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JPA, Hirschhorn JN. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet. 9:356-369; 2008.

38. Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux Ǥ ‡‘‡Ǧ™‹†‡ ƒ••‘…‹ƒ–‹‘ †‡ϐ‹‡• ‘”‡ –Šƒ ͵Ͳ †‹•–‹…– susceptibility loci for Crohns disease. Nat Genet. 40:955–962;

2008.

39. Esserlind A-L, Christensen AF, Le H, Kirchmann M, Hauge AW, Toyserkani NM, Hansen T, Grarup N, Werge T, Steinberg S, Bettella F, Stefansson H, Olesen J. Replication and meta-analysis of common

˜ƒ”‹ƒ–•‹†‡–‹ϐ‹‡•ƒ‰‡‘‡Ǧ™‹†‡•‹‰‹ϐ‹…ƒ–Ž‘…—•‹‹‰”ƒ‹‡Ǥ Eur J Neurol. 20:765-772; 2013.

40. Ligthart L, de Vries B, Smith A V, Ikram MA, Amin N, Hottenga J-J, Koelewijn SC, Kattenberg VM, de Moor MHM, Janssens ACJW, Aulchenko YS, Oostra BA, de Geus EJC, Smit JH, Zitman FG, Uitterlinden AG, Hofman A, Willemsen G, Nyholt DR, Montgomery GW, Terwindt GM, Gudnason V, Penninx BWJH, Breteler M, Ferrari MD, Launer LJ, van Duijn CM, van den Maagdenberg AMJM, Boomsma DI. Meta-analysis of genome-wide association for migraine in six population-based European cohorts. Eur J Hum Genet. 19:901-907; 2011.

41. Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, Yengo L, Lloyd-Jones LR, Sidorenko J, Wu Y, McRae AF, Visscher PM, Zeng J, Yang J.

Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nat Commun.

9:2941; 2018.

42. Fritsche LG, Igl W, Bailey JNC, Grassmann F, Sengupta S, Bragg-Gresham JL, Burdon KP, Hebbring SJ, Wen C, Gorski M, Kim IK, Cho D, Zack D, Souied E, Scholl HPN, Bala E, Lee KE, Hunter DJ, Sardell RJ, Mitchell P, Merriam JE, Cipriani V, Hoffman JD, Schick T, Lechanteur YTE, Guymer RH, Johnson MP, Jiang Y, Stanton CM, Buitendijk GHS, Zhan X, Kwong AM, Boleda A, Brooks M, Gieser L, Ratnapriya R, Branham KE, Foerster JR, Heckenlively JR, Othman MI, Vote BJ, Liang HH, Souzeau E, McAllister IL, Isaacs T, Hall J, Lake S, Mackey DA, Constable IJ, Craig JE, Kitchner TE, Yang Z, Su Z, Luo H, Chen D, Ouyang H, Flagg K, Lin D, Mao G, Ferreyra H, Stark K, von Strachwitz CN, Wolf A, Brandl C, Rudolph G, Olden M, Morrison MA, Morgan DJ, Schu M, Ahn J, Silvestri G, Tsironi EE, Park KH, Farrer LA, Orlin A, Brucker A, Li M, Curcio CA, Mohand-Saïd S, Sahel J-A, Audo I, Benchaboune M, Cree AJ, Rennie CA, Goverdhan S V, Grunin M, Hagbi-Levi S, Campochiaro P, Katsanis N, Holz FG, Blond F, Blanché H, Deleuze J-F, Igo RP, Truitt B, Peachey NS, Meuer SM, Myers CE, Moore EL, Klein R, Hauser MA, Postel EA, Courtenay MD, Schwartz SG, Kovach JL, Scott WK, Liew G, Tan AG, Gopinath B, Merriam JC, Smith RT, Khan JC, Shahid H, Moore AT, McGrath JA, Laux R, Brantley MA Jr, Agarwal A, Ersoy L, Caramoy A, Langmann T, Saksens NT, de Jong EK, Hoyng CB, Cain MS, Richardson AJ, Martin TM, Blangero J, Weeks DE, Dhillon B, van Duijn CM, Doheny KF, Romm J, Klaver CC, Hayward C, Gorin MB, Klein ML, Baird PN, den Hollander AI, Fauser S, Yates JR, Allikmets R, Wang JJ, Schaumberg DA, Klein BE, Hagstrom SA, Chowers I, Lotery AJ, Léveillard T, Zhang K, Brilliant MH, Hewitt AW, Swaroop A, Chew EY, Pericak-Vance MA, DeAngelis M, Stambolian D, Haines JL, Iyengar SK, Weber BH, Abecasis GR, Heid IM. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet. 48:134-143; 2016.

43. Bentham J, Morris DL, Cunninghame Graham DS, Pinder CL, Tombleson P, Behrens TW, Martín J, Fairfax BP, Knight JC, Chen L, Replogle J, Syvänen A-C, Rönnblom L, Graham RR, Wither JE, Rioux JD, Alarcón-Riquelme ME, Vyse TJ. Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus. Nat Genet. 47:1457-1464; 2015.

44. Mahajan A, Taliun D, Thurner M, Robertson NR, Torres JM, Rayner

9 Ec kardt K-U, Fischer K, Kardia SLR, Kronenberg F, Läll K, Liu C-T,

9 Ec kardt K-U, Fischer K, Kardia SLR, Kronenberg F, Läll K, Liu C-T,

In document Genetic predisposition to acute kidney injury in critically ill adults (sivua 73-112)