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Table 1 Annotation of credible set variants and genes in the 594 signals associated with eGFR

From: KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies

A

Annotation feature

PPA > 99% (# sig | #var | #genes)

PPA 50–99% (# sig | #var | #genes)

other variants in small sets (# sig | #var | #genes)

any other variants (# sig | #var | #genes)

Protein-relevant (all, VEP)

14 | 14 | 14

22 | 22 | 22

15 | 18 | 16

279 | 950 | 520

 Stop-gained/-lost; non-synonymous

10 | 10 | 10

16 | 16 | 16

6 | 6 | 6

127 | 271 | 197

 Canonical splice, noncoding change, synonymous, splice site

1 | 1 | 1

2 | 2 | 2

2 | 2 | 2

147 | 342 | 247

 Other (CADD-Phred ≥ 15)

3 | 3 | 3

4 | 4 | 4

9 | 10 | 9

169 | 344 | 217

eQTL kidney tissue (all)

11 | 11 | 14

28 | 28 | 41

24 | 61 | 28

239 | 13,025 | 520

 Tubulo-interstitium

10 | 10 | 11

22 | 22 | 30

21 | 54 | 23

205 | 10,472 | 400

 Glomerulus

7 | 7 | 10

18 | 18 | 26

15 | 38 | 16

195 | 10,562 | 362

 Kidney cortex

0 | 0 | 0

2 | 2 | 2

1 | 1 | 1

30 | 1,267 | 36

sQTL kidney cortex

0 | 0 | 0

0 | 0 | 0

1 | 1 | 1

13 | 522 | 23

Any of the above

23 | 23 | 27

47 | 47 | 61

31 | 70 | 39

348 | 13,576 | 865

B

Feature (source)

# genes

Genes with kidney phenotype in human (all sources)

235

 Online Mendelian Inheritance in Man (OMIM) genes

163

 Genes from sequencing CKD Patients (Groopman et al., 2019)

178

 Genes from sequencing ADTKD patients (Wopperer et al., 2022)

12

Genes with kidney phenotype in mouse models (MGI)

342

Gene is drug target in registered clinical trial (TTD)

499

 By trial with kidney disease indication

7

 By trial with any other indication

492

Any of the above

866

  1. The 35,885 variants in the 99% credible sets were queried for being protein-relevant or eQTL/sQTL in kidney tissue to any of the 5,906 genes; the 5,906 genes were queried for kidney phenotypes in human or mouse, and for drugability. A: Separating the variants by strength of statistical support, we show the number of variants that are protein-relevant [11, 16] or an eQTL/sQTL [17,18,19] in kidney tissue, the number of signals, and the number of mapped genes. B: Shown are the number of genes known for (i) causing a genetic disorder in human with kidney phenotype [21,22,23], (ii) a kidney phenotype in mouse [20] (iii) being drug target in registered clinical trials for kidney disease or any other diseases [24]
  2. Columns: “PPA > 99%”: exactly one variant in credible set; “PPA 50–99%”: variant has high PPA; “other variants in small set”: variant in small set that has PPA >  < 50%; “any other variants”: variants with PPA >  < 50% and set size > 5); Abbreviations: VEP: Variant effect predictor, CADD-Phred: Score for deleteriousness of a variant, eQTL: expression quantitative trait locus, sQTL: splice quantitative trait locus, #sig: number of signals, #var: number of variants in 99% credible sets
  3. CKD chronic kidney disease, ADTKD autosomal dominant tubulointerstitial kidney disease, MGI mouse genome informatics, TTD therapeutic target database
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BMC Bioinformatics

ISSN: 1471-2105

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