Genome-wide SNP analysis of the Systemic Capillary Leak Syndrome (Clarkson disease)

Figures & data

Table 1. Characteristics of study population

	Disease (n = 12)*	Controls (n = 18)
Males	8	10
Females	4	8
Mean age at enrollment (years ± S.D.)**	53.8 ± 6.9	46.5 ± 13.8***
Caucasian	12	16^&
Classic acute SCLS	11	NA
Chronic SCLS	1	NA
MGUS	10 (83%)	NA

* Diagnosis of SCLS made according to established criteria: at least one episode of hypotension, hemoconcentration (elevated Hgb/Hct), and hypoalbuminemia or chronic edema and hypoalbuminemia; **P = 0. 07, Mann-Whitney test;***does not include reference sample; ^&includes 1 Hispanic, 1 African-American.

Figure 1. Genome-wide analysis of 875,967 SNPs in 12 cases of SCLS and 18 control subjects. (A) Manhattan plot showing negative log-transformed P values of the case-control allele frequency significance on the y-axis. The color scale of the x-axis denotes chromosome numbers. Gene names associated with individual dots indicate SNPs of greatest significance or with potential disease relevance. (B) Distribution of 653 SNPs meeting the established criterion for genome-wide significance (P ≤ 1 × 10⁻³, Chi square test). (C) Expanded view of chromosomes 6–7, which contain regions of neighboring SNPs highly associated with SCLS.

Table 2. Highly ranked SNPs associated with SCLS

SNP	Gene	Chromosome	bp*	location	Minor allele (case frequency)	OR (95% CI)	P value**
rs6417039	LOC100130480	18	6568416	intron	A (0.54)	41.4 (4.8–352.9)	4.2 × 10^−6
rs3917490	PON1	7	94948841	intron	T (0.75)	12.4 (3.6–42.9)	1.9 × 10^−5
rs3130981	CDSN	6	31083813	exon (N527D)	T (0.58)	15.4 (3.7–64.6)	2.6 × 10^−5
rs12489170	PARP15	3	122354792	exon (G394R)	A (0.38)	NA***	6.8 × 10^−5
rs12355803	BTRC	10	103176449	intron	A (0.54)	13 (3.1–54.3)	8.4 × 10^−5
rs10239315	CHCHD3	7	132672067	intron	C (0.71)	8.5 (2.6–27.7)	1.8 × 10^−4
rs919751	PDGFRB	5	149505489	intron	G (0.63)	8.3 (2.5–27.8)	2.7 × 10^−4
rs11668246	ARHGEF18	19	7492991	intron	A (0.63)	8.7 (2.5–30.2)	2.9 × 10^−4
rs2364281	KBTBD8	3	67050203	intron	T (0.71)	7.3 (2.3–23.2)	4.5 × 10^−4
rs12552348	EDG2	9	113705204	intron	T (0.29)	NA	5.7 × 10^−4
rs4782779	CDH13	16	83402943	intron	A (0.46)	9.3 (2.2–38.9)	7.7 × 10^−4
rs12911414	RASGRF1	15	79343534	intron	G (0.58)	7 (2.1–23.1)	7.9 × 10^−4

* GRCh37.p5 assembly;**Chi-square test; ***Not applicable, detected only in cases.

Table 3. SCLS associated SNPs detected by both exome sequencing and SNP array

SNP	Gene	Chromosome	bp*	location	Minor allele (case frequency)	OR (95% CI)	P value**
rs386915	SERPINB1	6	2834265	intron	C (0.125)	0.16 (0.04–0.63)	5.2 × 10^−3
rs228274	PSMB3	17	36909061	5UTR^#	A (0.083)	0.161 (0.03–0.79)	0.015
rs1569767	SLC24A3	20	19261623	exon (V55I)	A (0.583)	3.64 (1.22- 10.8)	0.018
rs10883439	CPN1	10	101841153	intron	A (0.208)	9.21 (1–84.7)	0.022
rs1614065	MYOF	10	95097537	intron	T (0.167)	0.25 (0.07–0.88)	0.025
rs3752135	SIGLEC12	19	52000624	exon (Y376S)	T (0.25)	5.67 (1.03–31)	0.03
rs4799570	DSG4	18	28986333	exon (I644L)	A (0.375)	3.72 (1.06–13.05)	0.034
rs2274611	CTSL1	9	90342675	intron	T (0.667)	3.14 (1.07–9.27)	0.035
rs12185460	ARHGAP28	18	6898415	intron	C (0.292)	0.329 (0.11–0.99)	0.044

* GRCh37.p5 assemby; **Chi-square test; ^#5′ untranslated region

Table 4. Impact of non-synonymous mutations detected by SNP-chip and/or WES

SNP	Protein	Mutation	Frequency by WES (# positive/total)	PolyPhen annotation (score)	P value
rs3130981	CDSN	N527D	0/9	benign (0.004)	2.6 × 10^−5
rs12489170	PARP15	G394R / G628R*	4/9	probably damaging (1.0)	6.7 × 10^−5
rs1453547	OR5A2	P172L	7/9	probably damaging (0.997)	8.5 × 10^−4
rs8181512	OR52N2	H791R	9/9	probably damaging (0.991)	4 × 10^−3

* alternative splice variants; **Chi-square test

Table 5. Functional enrichment analysis of top ranked SNPs

Annotation terms	Enrichment score	#Genes*	Fold enrichment*	Select clustered genes	P value**
cell projection organization, neuron projection, cell projection	3.26	13	4.6	ATP2B2, NCK2, RASGRF1, DSCAM, CDH13, CTNNA2, CHRM3, KALRN, LPAR1	2.3 × 10^−5
synapse, cell junction, postsynaptic cell membrane	2.64	11	4	AFAP1, CTNNA2, CHRM3, CDSN, GRID1, GRIK1	3.9 × 10^−4
plasma membrane (part, integral, intrinsic)	2.6	34	2	ATP2B2, DSCAM, AFAP1, ADCY3, CDH13, CTNNA2, CHRM3, CDSN, EMCN, ITGA9, GNA14, LPAR1, PDGFRB, TRPA1	4.6 × 10^−5
pleckstrin homology domain, Rho and Ras regulation, RhoGEF	2.43	5	21	ARAP1, ASAP2, RASGRF1, ARHGEF18, AFAP1, ADCY3, BTRC, DGKB, KALRN, LPAR1, PON1	8.9 × 10^−5
fibronectin type III domain, immunoglobulin domain Ig-like C2 (types 1–2),	2.35	8	3.88	ADAMTSL1, CNTN3, NEO1, PDGFRB, PTPRD, ITGA9, CDH13, PCDH15, PCDH19	1.4 × 10^−4
cell adhesion, biological adhesion, cell-cell adhesion	2.19	9	3.3	DSCAM, CDH13, CTNNA2, CNTN3, CDSN, EMCN, ITGA9	5.5 × 10^−3

* For top cluster term; **EASE score (modified Fisher's exact test) for top cluster term

Figure 2. Functional enrichment of SCLS-associated SNPs. (A, B) 2-D heat maps representing genes containing SNPs significantly associated with SCLS and their associated functional annotation terms, as determined by the DAVID software algorithm. Related genes are portrayed on the x-axis and their corresponding annotations on the y-axis. Green areas represent positively reported gene-term association whereas black areas denote no gene-term association yet reported. Functionally enriched categories related to endothelial barrier dysregulation in SCLS included “cell projections” (A) and “cell adhesion” (B).

Figure 3. IPA network analysis reveals association of genes related to cytoplasmic/cytoskeletal organization. A list of 134 genes containing 653 SNPs associated with SCLS were uploaded for core analysis using Ingenuity Pathways Knowledge Base as reference. The network has been simplified for clear illustration of genes of interest. Colored symbol are genes contained on the list. Symbol shapes correspond to molecular functions as indicated. Direct or indirect interactions are shown by complete or dashed lines, respectively