LIFE Adult-Studie

​​​​​​​​​Die LIFE Adult-Studie ist eine langfristig angelegte, bevölkerungsbezogene Kohortenstudie. Stichproben aus der Leipziger Erwachsenenbevölkerung werden hinsichtlich vielfältiger Merkmale und Krankheitsrisiken umfassend untersucht. Insbesondere die Häufigkeit von Volkskrankheiten steht im Mittelpunkt der Forschungsarbeiten. Der Einfluss von Lebensstil- und Umweltfaktoren auf diese Erkrankungen wird charak​terisiert. Bisher unbekannte Risikofaktoren für die Entstehung von Volkskrankheiten sollen aufgespürt und neue Möglichkeiten der Früherkennung entwickelt werden.

Die Forschungsschwerpunkte liegen dabei unter anderem

  • auf dem Herz-Kreislauf-System,
  • in der Erforschung von Kognition und Demenzerkrankungen,
  • in der Erforschung früher Formen der altersbedingten depressiven Symptomatik und Depression sowie des Zusammenhanges zwischen Depression und Wachheit,
  • auf der Identifikation von Lebensstil-, Risiko- und Schutzfaktoren für die Dynamik der Entwicklung der verschiedenen Formen des Übergewichtes und der Erforschung von damit verbundenen Veränderungen im Gehirn,
  • in der Untersuchung früher Formen altersbedingter Veränderungen am Auge sowie
  • in der Erforschung von Allergien und Immunkompetenz.
Die Ergebnisse der LIFE Adult-Studie gewähren einen tiefen Einblick in die Gesundheit der erwachsenen Bevölkerung in Leipzig. Damit können wir auch die Voraussetzung für eine Gesundheitsberichterstattung und Grundlagen für zukünftige Planungen von präventiven und supportiven Maßnahmen schaffen.​

Highlights in Publikationen

Bisherige Ergebnisse der LIFE Adult-Studie – Highlights in Publikationen

​1. Loeffler M, Engel C, Ahnert P et al. The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany. BMC Public Health 2015;15:691.

2. Enzenbach C, Wicklein B, Wirkner K, Loeffler M. Evaluating selection bias in a population-based cohort study with low baseline participation: the LIFE-Adult-Study. BMC Med Res Methodol 2019;19:135.

3. Kharabian Masouleh S, Arelin K, Horstmann A et al. Higher body mass index in older adults is associated with lower gray matter volume: implications for memory performance. Neurobiol Aging 2016;40:1–10.

4. Schaare HL, Kharabian Masouleh S, Beyer F et al. Association of peripheral blood pressure with gray matter volume in 19- to 40- year-old adults. Neurology 2019;92:e758–73.

5. Beyer F, Kharabian Masouleh S, Kratzsch J et al. A metabolic obesity profile is associated with decreased gray matter volume in cognitively healthy older adults. Front Aging Neurosci 2019; 11:202.

6. Zhang R, Beyer F, Lampe L et al. White matter microstructural variability mediates the relation between obesity and cognition in healthy adults. Neuroimage 2018;172:239–49.

7. Beyer F, Garcia-Garcia I, Heinrich M et al. Neuroanatomical correlates of food addiction symptoms and body mass index in the general population. Hum Brain Mapp 2019;40:2747–58.

8. Beyer F, Kharabian Masouleh S, Huntenburg JM et al. Higher body mass index is associated with reduced posterior default mode connectivity in older adults. Hum Brain Mapp 2017;38:3502–15.

9. Beyer F, Zhang R, Scholz M et al. Higher BMI, but not obesityrelated genetic polymorphisms, correlates with lower structural connectivity of the reward network in a population-based study. Int J Obes (Lond) 2021;45:491–501.

10. Kharabian Masouleh S, Beyer F, Lampe L et al. Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. J Cereb Blood Flow Metab 2018;38: 360–72.

11. Thomas K, Beyer F, Lewe G et al. Higher body mass index is linked to altered hypothalamic microstructure. Sci Rep 2019;9: 17373.

12. Lampe L, Zhang R, Beyer F et al. Visceral obesity relates to deep white matter hyperintensities via inflammation. Ann Neurol 2019;85:194–203.

13. Zsido RG, Heinrich M, Slavich GM et al. Association of estradiol and visceral fat with structural brain networks and memory performance in adults. JAMA Netw Open 2019;2:e196126.

14. Luck T, Then FS, Schroeter ML et al. Prevalence of DSM-5 mild neurocognitive disorder in dementia-free older adults: results of the population-based LIFE-Adult-Study. Am J Geriatr Psychiatry 2017;25:328–39.

15. Luck T, Roehr S, Rodriguez FS et al. Memory-related subjective cognitive symptoms in the adult population: prevalence and associated factors: results of the LIFE-Adult-Study. BMC Psychol 2018;6:23.

16. Luck T, Pabst A, Rodriguez FS et al. Age-, sex-, and educationspecific norms for an extended CERAD Neuropsychological Assessment Battery: results from the population-based LIFEAdult-Study. Neuropsychology 2018;32:461–75.

17. Luck T, Then FS, Luppa M et al. Association of the apolipoprotein E genotype with memory performance and executive functioning in cognitively intact elderly. Neuropsychology 2015;29: 382–87.

18. Kuehnapfel A, Ahnert P, Loeffler M, Broda A, Scholz M. Reliability of 3D laser-based anthropometry and comparison with classical anthropometry. Sci Rep 2016;6:26672.

19. Loffler-Wirth H, Willscher E, Ahnert P et al. Novel anthropometry based on 3D-bodyscans applied to a large population based cohort. PLoS One 2016;11:e0159887.

20. Frenzel A, Binder H, Walter N, Wirkner K, Loeffler M, Loeffler-Wirth H. The aging human body shape. NPJ Aging Mech Dis 2020;6:5.

21. Kuehnapfel A, Ahnert P, Loeffler M, Scholz M. Body surface assessment with 3D laser-based anthropometry: reliability, validation, and improvement of empirical surface formulae. Eur J Appl Physiol 2017;117:371–80.

22. Wang M, Elze T, Li D et al. Age, ocular magnification, and circumpapillary retinal nerve fiber layer thickness. J Biomed Opt 2017;22:1–19.

23. Li D, Rauscher FG, Choi EY et al. Sex-specific differences in circumpapillary retinal nerve fiber layer thickness. Ophthalmology 2020;127:357–68.

24. Baniasadi N, Rauscher FG, Li D et al. Norms of interocular circumpapillary retinal nerve fiber layer thickness differences at 768 retinal locations. Trans Vis Sci Tech 2020;9:23.

25. Rauscher FG, Wang M, Francke M et al. Renal function and lipid metabolism are major predictors of circumpapillary retinal nerve fiber layer thickness-the LIFE-Adult Study. BMC Med 2021;19:202.

26. Berger T, Fuchs M, Dippold S et al. Standardization and feasibility of voice range profile measurements in epidemiological studies. J Voice 2022;36:142 e9–20.

27. Berg M, Fuchs M, Wirkner K, Loeffler M, Engel C, Berger T. The speaking voice in the general population: normative data and associations to sociodemographic and lifestyle factors. J Voice 2017;31:257.e13–24.

28. Jost L, Fuchs M, Loeffler M et al. Associations of sex hormones and anthropometry with the speaking voice profile in the adult general population. J Voice 2018;32:261–72.

29. Wilkinson MD, Dumontier M, Aalbersberg IJ et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016;3:160018. International Journal of Epidemiology, 2022, Vol. 00, No. 00 13 Downloaded from https://academic.oup.com/ije/advance-article/doi/10.1093/ije/dyac114/6594394 by Universitaetsbibliothek user on 30 May 2022

30. Dogan-Sander E, Willenberg A, Batmaz I et al. Association of serum 25-hydroxyvitamin D concentrations with sleep phenotypes in a German community sample. PLoS One 2019;14:e0219318.

31. Spada J, Sander C, Burkhardt R et al. Genetic association of objective sleep phenotypes with a functional polymorphism in the neuropeptide S receptor gene. PLoS One 2014;9:e98789.

32. Jawinski P, Sander C, Mauche N et al. Brain arousal regulation in carriers of bipolar disorder risk alleles. Neuropsychobiology 2015;72:65–73.

33. Jawinski P, Tegelkamp S, Sander C et al. Time to wake up: No impact of COMT Val158Met gene variation on circadian preferences, arousal regulation and sleep. Chronobiol Int 2016;33: 893–905.

34. Jawinski P, Kirsten H, Sander C et al. Human brain arousal in the resting state: a genome-wide association study. Mol Psychiatry 2019;24:1599–609.

35. Spada J, Scholz M, Kirsten H et al. Genome-wide association analysis of actigraphic sleep phenotypes in the LIFE Adult Study. J Sleep Res 2016;25:690–701.

36. Pott J, Burkhardt R, Beutner F et al. Genome-wide meta-analysis identifies novel loci of plaque burden in carotid artery. Atherosclerosis 2017;259:32–40.

37. Buchmann N, Scholz M, Lill CM et al. Association between lipoprotein(a) level and type 2 diabetes: no evidence for a causal role of lipoprotein(a) and insulin. Acta Diabetol 2017;54:1031–38.

38. Davies G, Lam M, Harris SE et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun 2018;9:2098.

39. Franceschini N, Giambartolomei C, de Vries PS et al.; MEGASTROKE Consortium. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes. Nat Commun 2018;9:5141.

40. Vojinovic D, Adams HH, Jian X et al. Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume. Nat Commun 2018;9:3945.

41. Walker CJ, Oakes CC, Genutis LK et al. Genome-wide association study identifies an acute myeloid leukemia susceptibility locus near BICRA. Leukemia 2019;33:771–75.

42. Wuttke M, Li Y, Li M et al.; V. A. Million Veteran Program. A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat Genet 2019;51:957–72.

43. Pott J, Bae YJ, Horn K et al. Genetic association study of eight steroid hormones and implications for sexual dimorphism of coronary artery disease. J Clin Endocrinol Metab 2019;104: 5008–23.

44. Pott J, Schlegel V, Teren A et al. Genetic regulation of PCSK9 (Proprotein Convertase Subtilisin/Kexin Type 9) plasma levels and its impact on atherosclerotic vascular disease phenotypes. Circ Genom Precis Med 2018;11:e001992.

45. Pott J, Beutner F, Horn K et al. Genome-wide analysis of carotid plaque burden suggests a role of IL5 in men. PLoS One 2020;15: e0233728.

46. Schmidt M, Hopp L, Arakelyan A et al. The human blood transcriptome in a large population cohort and its relation to aging and health. Front Big Data 2020;3:548873.

47. Vosa U, Claringbould A, Westra HJ et al.; i2QTL Consortium. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet 2021;53:1300–10.

48. Dittrich J, Adam M, Maas H et al. Targeted on-line SPE-LC-MS/ MS assay for the quantitation of 12 apolipoproteins from human blood. Proteomics 2018;18:1700279.

49. Reinicke M, Schroter J, Muller-Klieser D, Helmschrodt C, Ceglarek U. Free oxysterols and bile acids including conjugates: simultaneous quantification in human plasma and cerebrospinal fluid by liquid chromatography-tandem mass spectrometry. Anal Chim Acta 2018;1037:245–55.

 50. Bae YJ, Zeidler R, Baber R et al. Reference intervals of nine steroid hormones over the life-span analyzed by LC-MS/MS: effect of age, gender, puberty, and oral contraceptives. J Steroid Biochem Mol Biol 2019;193:105409.

51. Melzer S, Zachariae S, Bocsi J, Engel C, Löffler M, Tarnok A. Reference intervals for leukocyte subsets in adults: results from a population-based study using 10-color flow cytometry. Cytometry B Cytometry 2015;88:270–81.

52. Wichmann G, Gaede C, Melzer S et al. Discrimination of head and neck squamous cell carcinoma patients and healthy adults by 10-color flow cytometry: development of a score based on leukocyte subsets. Cancers (Basel) 2019;11:814.

53. Zeynalova S, Bucksch K, Scholz M et al. Monocyte subtype counts are associated with 10-year cardiovascular disease risk as determined by the Framingham Risk Score among subjects of the LIFE-Adult study. PLoS One 2021;16:e0247480.

54. Bocsi J, Melzer S, Dahnert I, Tarnok A. OMIP-023: 10-color, 13 antibody panel for in-depth phenotyping of human peripheral blood leukocytes. Cytometry A 2014;85:781–84.


Weitere Informationen zur LIFE Adult Basisuntersuchung sowie den Folgeuntersuchungen finden Sie hier:


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Kontakt:

LIFE Studienambulanz für Erwachsene
Medizinische Fakultät der Universität Leipzig
Philipp-Rosenthal-Str. 27/EG
04103 Leipzig

​Telefon: 0341 - 97 16718
E-Mail: adult-info@life.uni-leipzig.de​​



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Philipp-Rosenthal-Str. 27, Haus M
04103 Leipzig
Telefon:
0341 - 97 16 720
Fax:
0341 - 97 16 729
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