Table 3.

Genetically predicted gene expression results from GWAS summary statistics

Tissue	Gene	Chr	Z score	P value	R 2a	Varianceb	N SNPsc	Model Nd
Thyroid	CYTH4*	22	−5.42	5.86E−08	0.030	0.0003	1	17
Breast	ZNF391	6	4.40	1.07E−05	0.157	0.008	6	17
Thyroid	AGT	1	−4.22	2.49E−05	0.010	0.005	6	50
Whole blood	SLC26A8	6	4.08	4.43E−05	0.046	0.001	4	14
Fibroblasts	ZNF391	6	4.04	5.34E−05	0.519	0.123	34	77
Ovary	ZNF391	6	3.97	7.17E−05	0.315	0.110	14	26
Whole blood	ALDH2	12	3.97	7.30E−05	0.008	0.002	8	42
Breast	LY6D*	8	−3.79	1.52E−04	0.046	0.001	6	35
Fibroblasts	MOB3A	19	3.77	1.62E−04	0.008	0.0002	2	11
Subcutaneous adipose	GLIS1	1	−3.75	1.75E−04	0.034	0.0002	2	6
Whole blood	ZNF391	6	3.70	2.13E−04	0.103	0.001	12	32
Subcutaneous adipose	ZNF391	6	3.69	2.20E−04	0.225	0.038	6	33
Fibroblasts	FAM174A	5	−3.66	2.51E−04	0.040	0.004	8	48
Vagina	ZNF391	6	3.65	2.63E−04	0.193	0.037	23	39
Breast	OAZ1	19	3.61	3.11E−04	0.019	0.013	11	42
Thyroid	ZNF391	6	3.57	3.60E−04	0.317	0.023	26	57
Thyroid	RAB30	11	3.53	4.21E−04	0.062	0.047	33	89
Vagina	UCKL1	20	3.53	4.22E−04	0.100	0.123	24	113
Whole blood	TMEM91	19	3.52	4.28E−04	0.180	0.0009	2	10

Boldface highlights suggestive predicted ZNF391 expression across multiple tissues

^* represents genes which localize to top GWAS signals (Table 2)

^aPerformance prediction R ²

^bVariance of the gene’s predicted expression, calculated as W′ × G × W (where W is the vector of SNP weights in a gene’s model, W′ is its transpose, and G is the covariance matrix)

^cNumber of SNPs included in the prediction model for that gene available in the summary statistics

^dNumber of SNPs used to construct the prediction model for the gene in the tissue of interest using the GTEx data