Identification of novel candidate variants including COL6A6 polymorphisms in early-onset atopic dermatitis using whole-exome sequencing

Peripheral blood samples were obtained from three families with a history of AD. Each family consists of 2 affected and 2 unaffected individuals (Additional file 1: Figure S1). We attempted to eliminate environmental factors as much as possible by recruiting early-onset cases. This study was reviewed and approved by the Chung-Ang University Hospital Institutional Review Board. Each family member was diagnosed with AD by a dermatologist. All patients and children developed AD before 2 years of age and were selected based on high IgE level (>1000) and SCORAD score (>50). Additionally, 112 AD patients and 61 control subjects under 2 years 9 months old were enrolled to validate the association between the candidate variants and atopic dermatitis (Additional file 1: Table S1).

Genomic DNA was isolated from the peripheral blood of the members of the three families using a QIAamp DNA Mini Kit (Qiagen Inc, Valencia, CA, USA). The DNA quality and quantity were assessed with a Nanodrop spectrometer (Nanodrop Technologies, Wilmington, DE, USA) and a Qubit fluorometer (Life Technologies, Grand Island, NY, USA). WES was performed using SureSelect Human All Exon V4 + UTR 71 Mb (Agilent, CA, USA), following the manufacturer’s standard protocol. Genomic DNA was sheared using Covaris (Covaris, Woburn, MA, USA). A paired-end DNA sequencing library was prepared through shearing, end-repair, A-tailing, peak detection, PE adaptor ligation, and amplification. After the library was hybridized with bait sequences for 24 h, it was purified and amplified with an index barcode tag, and the library quality and quantity were determined. The exome library was sequenced with the 100-bp paired-end mode of the HiSeq SBS kit.

Sequence reads in FASTQ format were mapped to the human assembly UCSC hg19 using the Burrows-Wheeler Aligner (BWA, v0.7.7) [12] with “mem” and seed value parameters “-k 45” to create SAM files with correct mate pair information. The read group tag included the sample name. Picard (v1.92) was then used to convert the SAM files to compressed BAM files and then to sort the BAM files by chromosome coordinate. The Genome Analysis Toolkit (v2.3.9Lite) [13] was used to locally realign the BAM files at intervals corresponding to potential insertion/deletion (indel) alignment errors. Insertions and deletions were identified with Mutect [14] and a GATK Somatic Indel Detector, respectively. Single-nucleotide variants and indels were annotated using snpEff (v3.6c) [15] to classify variants as synonymous, non-synonymous, missense, frameshift point mutations, or frameshift indels.

Filter 1: SnpEff (http://​snpeff.​sourceforge.​net/​index.​html) is a type of variant annotation and an effect prediction tool. It annotates and predicts the effects of variants, such as amino acid changes, on genes. Variants produce effects of different “types” (e.g., non-synonymous, stop-gained, insertion, deletion).

Filter 2: Impact prediction by SnpEff shows results of putative variants, making it easier to quickly categorize and prioritize variants (High: Splice_Site_Acceptor, Splice_Site_Donor, Start_Lost, Frame_Shift, Stop_Gained; Moderate: Non_Synonymous_coding, Codon_Change, Codon_Insertion and Deletion, etc.).

Filter 3: SIFT and Polyphen2 of dbNSFP

The SIFT score predicts whether an amino acid substitution affects protein function. SIFT prediction is based on the degree of amino acid conservation in aligned segments derived from closely related sequences, as collected through PSI-BLAST. The range was 0 to 1; substitutions with scores lower than 0.05 were predicted to be damaging (a lower score signified a greater detrimental effect), whereas substitutions with higher scores were predicted to be tolerable.

The Polyphen2 HDIV score was based on HumDiv, i.e., hdiv_prob. The score ranged from 0 to 1, and a higher score suggested a greater degree of predicted damage. A prediction of “probably damaging” corresponded to scores between 0.957 and 1, “possibly damaging” for scores ranging from 0.453 to 0.956, and “benign” for those between 0 and 0.452.

Filter 4: The PhyloP of dbNSFP detects sites under negative or positive selection while allowing for changes in evolution rate over the branches of the phylogenetic tree. A higher PhyloP score indicates a better conserved site (http://​varianttools.​sourceforge.​net/​Annotation/​DbNSFP).

Filter 5: PhastCons measures the strength of purifying selection acting on a DNA sequence. A high PhastCons score (0.2) is strong evidence that a genomic region is functionally important.

Filter 6: The 1000 Genome allele frequency of dbNSFP selects variants with frequencies of less than 0.01 or those with unknown frequencies.

Filter 7: The in-house Korean database at the Theragen Etex Bio Institute selects variants with minor allele frequencies (MAFs, less than 0.02 or unknown).

Three SNPs were selected for Sanger validation. PCR amplification of all SNPs was performed at 95 °C for 10 min, followed by 35 cycles at 95 °C for 30 s, 55–58 °C for 30 s and 72 °C for 40 s, with a final extension at 72 °C for 1 min 30 s. The PCR mixtures (total volume 50 μL) contained 25 μL of 2X EF-Taq premix (SolGent, Seoul, South Korea), 2.5 μL of oligonucleotide primer (10 pmol/μL), 18 μL of distilled water, and 2 μL of template containing 20 ng genomic DNA. The PCR products underwent purification via a PCR purification kit (Favorgen, Pingtung, Taiwan) and were sequenced on an Applied Biosystems 3500 DNA sequencer (Foster City, CA, USA) according to the manufacturer’s instructions.

WES was performed on three families with AD. To limit our study to genetic factors, we recruited three pedigrees from families with severe clinical AD phenotypes and attempted to minimize environmental factors by selecting early-onset cases. The WES analysis showed that all affected individuals were heterozygous for the identified variants, while unaffected individuals were homozygous wild-type (Table 1).

A large amount of WES data from each individual exome were filtered in a stepwise fashion to isolate candidate variants related to AD (Additional file 1: Figure S2). The variants collected from the three families were counted after each filtering process. We obtained an average of 176 common variants per family after filter 4 and an average of 48 rare variants following the 1000 Genome filter 5. An average of 44 rare variants were detected after the Korean filter (Table 2).

Amino acid changes and variant types (non-synonymous SNP, stop-gained, insertion, deletion) were determined using the variant annotation from the step 1 filter. A non-synonymous SNP is a single-nucleotide change that results in a codon for a different amino acid. Considerable numbers of non-synonymous SNPs were observed in the three families (data not shown).

The variants identified by filter 5 not only indicated common variants (MAF greater than 1%), but also possible functional variants predicted to impair protein function as well as sequences that are highly conserved among 100 vertebrate species.

To find more critical variants among the many filtered genes, we confirmed the overlapping genes of common variants from filter 5 in the three families (Table 1 and Additional file 1: Figure S3). There were 14 overlapping genes in filter 5, four of which reached filter 7 and could be called “rare variants.” Risk alleles were identified in AD patients by comparison with healthy controls (Table 1). The number of overlapping genes is also depicted as a Venn diagram (Additional file 1: Figure S3). Variants of COL6A6 appeared in all three families (Tables 3, 4 and 5), and two COL6A6 SNPs were detected in Family A (Table 3).

The genotypes of the 14 genes were further assessed in an exome analysis. Affected fathers and children were heterozygous, while unaffected mothers and children were homozygous wild type for all 14 candidate genes (Table 1).

The chromosome position, amino acid change, and functional prediction score for each of the 14 overlapping genes are presented for each family. The 14 candidate genes were deemed functionally interesting and supported by the SIFT scores (probability of being damaging/deleterious) and the results of the PhyloP analysis (highly conserved among 100 vertebrate species). The significantly low SIFT and high PhyloP and Phastcon scores of COL6A6 found in all three families signify deleterious protein function. Furthermore, when the Korean filter was applied to COL6A6, all three families showed a genetic variant with an MAF range of 1.7–18%, as measured in 800 Koreans subjects (Tables 3, 4 and 5).

To reduce errors from WES, COL6A6 was analyzed by Sanger sequencing to detect SNPs in all three families. The variants we identified were in positions consistent with those of the WES results. In Family A, the missense mutations c.5216G > A, p.Arg1739Glu (common variant), and c.2716C > T, p.Arg906Cys (rare variant) were detected in the affected family members, but not in unaffected family members (Fig. 1a and b). In Family B, the missense mutation c.1666C > T, p.Pro555Ser (common variant) was only found in the affected members (Fig. 1c). In Family C, the missense mutation c.2716C > T, p.Arg906Cys (rare variant) was also only detected in the affected members (Fig. 1d).

Additionally, to investigate the possibility of COL6A6 variants (rs16830494, rs59021909, and rs200963433) as candidate risk factors for AD, Sanger sequencing was also performed in a case-control study involving 112 patients with AD and 61 control subjects. The allele and genotype frequencies were counted (Table 6). Odds ratios (OR) and 95% confidence intervals (CI) were estimated for all risk factors (Additional file 1: Table S2). No significant associations were found in these three variants under either dominant or recessive models. However, a minor allele (A) of the common variant rs16830494 showed a tendency toward lower frequency. Homozygosity for the rs16830494 minor allele (AA) and for the rs59021909 (TT) allele were more frequent in AD cases compared to controls. The rs200963433 is a rare variant; the 3.5% heterozygous frequency (CT) of rs200963433 seen in the AD cases was double the 1.6% frequency observed in healthy controls (Table 6). The frequency of rs200963433 in Sanger sequencing was also compared with the frequency of 1000 global, 286 East Asian, and 800 Korean subjects. The 1.7% MAF of rs200963433 in the 800 Koreans surveyed nearly matched that of the 61 health controls in Sanger sequencing, and the MAF was elevated in AD cases (Tables 3 and 6).

We compared the genetic loci between AD candidate variants identified via WES and in AD-linked chromosomal regions. In previous studies, AD-related chromosome loci were detected using AD linkage analysis. The CDX1, ANKRD35, and TUFT1 genes were present at positions 5q31-33 and 1q21. COL6A6 was in close proximity to the 3q21 locus, which is known to be linked to AD (Table 7).

We also detected SNPs in filaggrin (FLG) and FLG2 in these three families. FLG polymorphisms at the 1q21 locus were observed in three families, respectively (Additional file 1: Table S3).