Skip to main content

Table 3 Significant WES-WGS SKAT meta-analysis results for genes enriched for PAVs (p<2.9×10−6) or PTVs (p<1×10−5) using SKAT or VT algorithms

From: Whole-exome sequencing identifies novel protein-altering variants associated with serum apolipoprotein and lipid concentrations

    

SKAT

VT

GENE

Type

Pheno

N

Nvar

PLiu

Nvar

MAF cutoff

Effect

P

DEFT1P

PTV

VLDLPL XL

445

1

1.23×10−6

1

0.020

1.157

1.23×10−6

SBDS

PTV

apoC-III

617

2

5.37×10−6

2

0.005

1.692

1.86×10−5

LIPC

PAV

apoA1

918

6

1.48×10−7

4

0.017

1.004

2.12×10−8

GTF3C5

PAV

Non-HDLC

919

8

6.86×10−7

8

0.007

−0.536

0.014

  

LDL Friedewald

920

8

9.27×10−7

8

0.007

−0.705

1.35×10−3

  

Total cholesterol

920

8

1.30×10−6

8

0.007

−0.522

0.016

TRMT5

PAV

VLDLPL XS

738

8

7.87×10−7

8

0.007

−0.985

3.20×10−7

RBM47

PAV

apoC-III

617

3

1.33×10−6

3

0.005

−1.228

7.20×10−4

RYR3

PAV

VLDLTG XS

748

25

1.30×10−4

24

0.009

0.530

2.08×10−6

MARCH10

PAV

VLDLPL XS

748

5

1.14×10−5

4

0.003

−1.498

2.24×10−6

  1. Type burden of PAVs or PTVs, Nvar number of variants of the given variant type, PLiuP-value for SKAT gene burden, calculated with Liu method, Effect pooled effect size estimate β from the VT test, VLDLPL XS/XL phospholipid in extra small/extra-large VLDL, VLDLTG XS triglycerides in extra small VLDL particles