glycans and age dealing with non-linear correlations lucija klarić genos ltd. lucija klarić
TRANSCRIPT
![Page 1: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/1.jpg)
Glycans and ageDealing with non-linear correlations
Lucija KlarićGenos Ltd.
Lucija Klarić
![Page 2: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/2.jpg)
Relationship between age and glycans
![Page 3: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/3.jpg)
Local correction for age and sex- linear age/sex correction vs local age/sex correction- local age/sex correction – general additive models with smooth function
(R package: mgcv)
![Page 4: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/4.jpg)
Local correction for age and sexResiduals after age and sex correction in Korcula cohort
![Page 5: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/5.jpg)
Local correction for age and sexResiduals after age and sex correction in Korcula cohort
![Page 6: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/6.jpg)
Materials and methods• 2 cohorts:– Korcula
• 851 individuals• 316751 SNPs (typed)• 77 glycans (UPLC)
– Vis• 808 individuals• 308996 SNPs (typed)• 77 glycans (UPLC)
• GWAS – GenABEL package for R• Meta analysis – MetABEL package for R
![Page 7: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/7.jpg)
Comparison GWAS Korcula: Linear vs Local Correction
SNP glycan p (Linear) p (Local)rs6764279 IGP29 4.68E-31 2.59E-31rs6764279 IGP35 5.49E-19 7.30E-19rs6764279 IGP32 3.10E-17 2.39E-17rs6764279 IGP15 9.69E-17 2.05E-16rs12366899 IGP41 2.80E-16 2.40E-16rs12366899 IGP1 3.09E-15 3.38E-15rs6444193 IGP29 2.09E-14 3.92E-14rs6939603 IGP41 3.28E-14 1.56E-14rs6764279 IGP28 3.73E-14 5.77E-14rs6939603 IGP1 9.47E-14 3.68E-14rs6764279 IGP24 2.93E-13 3.95E-13rs11621121 IGP42 1.02E-12 2.07E-11rs12366899 IGP19 1.38E-12 2.15E-13
![Page 8: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/8.jpg)
Comparison Meta analysis: Linear vs Local Correction
SNP glycan p (Linear) p (Local) chi (Linear) chi (Local) chi Lin/Locrs6764279 IGP29 9.07E-59 1.46E-58 261.27 260.32 1.004rs6764279 IGP15 2.24E-36 5.10E-35 158.65 152.43 1.041rs6764279 IGP35 9.90E-35 9.00E-35 151.11 151.30 0.999rs6764279 IGP32 1.78E-29 2.63E-30 127.09 130.88 0.971rs6764279 IGP28 4.34E-29 2.02E-28 125.31 122.26 1.025rs6444193 IGP29 2.49E-25 6.23E-25 108.15 106.33 1.017rs6764279 IGP24 6.00E-24 4.76E-23 101.85 97.74 1.042rs4686837 IGP29 1.04E-19 7.36E-20 82.53 83.22 0.992rs909674 IGP39 2.52E-18 6.64E-18 76.24 74.32 1.026rs909674 IGP40 3.84E-18 9.26E-18 75.40 73.66 1.024rs11621121IGP59 1.29E-16 5.09E-15 68.47 61.22 1.118rs12366899IGP41 3.19E-16 2.60E-16 66.69 67.08 0.994
![Page 9: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/9.jpg)
Concluding remarks
• Most p-values are lower in linear correction than local correction for age
• Linear age correction outperformes local age correction– possible reason: local correction corrects better only
few people (~50 people from 40-50 years of age)• Associations of SNPs and glycans are quite robust• Residuals of local correction for age and sex are
not related to age
![Page 10: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/10.jpg)
Monogalactosylated IgG glycans in agingβ4GalT-I (Beta-1,4-galactosyltransferase 1) • adds galactose to GlcNAc residues• interacts preferentially with 1,6-arm
FA2[6]G1 FA2[3]G1FA2B[6]G1 FA2B[3]G1
![Page 11: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/11.jpg)
Monogalactosylated structures with Gal on 1,6 arm decrease with age.Monogalactosylated structures with bisecting GlcNAc with Gal on 1,3 or 1,6 arm increase with age.
Monogalactosylated IgG glycans in aging
![Page 12: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/12.jpg)
Monogalactosylated structures with Gal on 1,6 arm decrease with age.Monogalactosylated structures with bisecting GlcNAc with Gal on 1,3 or 1,6 arm increase with age.
Glycan KOR (n=915) ORCADES (n=2035) Twins (n=1261) VIS (n=906)R p R p R p R p
FA2[6]G1 -0.193 6.49E-08 -0.171 1.92E-12 -0.028 6.86E-03 -0.231 2.71E-11FA2[3]G1 0.010 3.91E-01 0.024 3.89E-08 0.008 2.30E-03 -0.061 9.06E-02FA2B[6]G1 0.141 2.33E-07 0.335 4.69E-46 0.183 2.79E-10 0.043 1.69E-01FA2B[3]G1 0.264 1.05E-17 0.481 4.31E-113 0.314 3.77E-27 0.247 5.36E-14
Table 1. Associations of glycans with age (UPLC)
Monogalactosylated IgG glycans in aging
![Page 13: Glycans and age Dealing with non-linear correlations Lucija Klarić Genos Ltd. Lucija Klarić](https://reader036.vdocuments.site/reader036/viewer/2022062409/5697bfc91a28abf838ca92df/html5/thumbnails/13.jpg)
Table 2. Correlation of age and glycans measured by different methods in Vis population (500 subjects).
Glycan UPLC xCGE-LIF
(Total IgG) (Total IgG)R p R p
FA2[6]G1 -0,303 8,19E-11 -0,218 3,69E-06FA2[3]G1 -0,094 4,91E-02 -0,026 5,79E-01FA2B[6]G1 -0,021 6,63E-01 0,012 8,01E-01FA2B[3]G1 0,254 6,37E-08 0,302 8,86E-11
Glycan MALDI-TOF-MS LC-ESI-MS
IgG1 IgG2&3 IgG1 IgG2&3R p R p R p R p
FA2[6]G1FA2[3]G1
-0,506 4,64E-30 -0,568 4,35E-39 -0,088 6,50E-02 -0,390 1,58E-17
FA2B[6]G1FA2B[3]G1
-0,154 1,15E-03 -0,412 1,49E-19 -0,008 8,72E-01 -0,247 1,48E-07
Monogalactosylated IgG glycans in aging