Gene, genetics and genetic medicines in gastroenterology: Current status and its future

Table 7 Methods for genetic testing and its clinical implication[35-55]

Test	Detects	Clinical use	Benefit	Limitation	Ref.
Cytogenetic testing
Karyotyping (conventional cytogenetics)	Detects large chromosomal abnormalities: Trisomies, translocations, deletions, G-banding of metaphase chromosomes	Down syndrome, Turner syndrome	Whole-genome overview, identifies balanced/unbalanced rearrangements	Low resolution, cannot detect small deletions/duplications, requires dividing cells	Genetic Alliance[35]
Fluorescence in situ hybridization (FISH)	Fluorescent probes bind specific DNA sequences on chromosomes	Detects gene amplifications, deletions, rearrangements (e.g., HER2 in gastric cancer, ALK in GI stromal tumors)	Rapid, targeted, works on interphase cells	Limited to known targets, one probe/test, cannot assess whole genome	Yilmaz and Demiray[36]
Comparative genomic hybridization (aCGH)	DNA from patient and control hybridized to a microarray	Detects copy number variations (e.g., deletions in polyposis syndromes, microdeletion syndromes	High-resolution, genome-wide, detects sub microscopic CNV	Cannot detect balanced rearrangements (e.g., translocations), limited to CNVs only	Weiss et al[37]
Chromosomal microarray analysis	aCGH + SNP array	Used in syndromic GI diseases, unexplained developmental delay, congenital anomalies	Genome-wide, detects CNVs, uniparental disomy, mosaicism	Cannot detect balanced rearrangements, may report VUS	Myllykangas et al[38]
Spectral karyotyping	Whole chromosome painting with multicolor FISH	Identifies complex chromosomal rearrangements, often in cancers	Detects complex karyotypes, color-coded analysis	Expensive, not used for routine diagnostics, lower resolution than aCGH	Guo et al[39]
Molecular genetic testing
Sanger sequencing	SNV, small insertions/deletions	Confirmatory testing (e.g., known APC, MLH1 mutations	High accuracy for point mutation or small deletion/duplication/SNV, cost effective for single genetic testing	Only identify small subset of gene or single gene, not precisely quantifiable	Herpich et al[40]
NGS	Panel, exome, or genome-wide variants	Multigene panels for IBD, polyposis, CRC, gastric cancer, GIST	Multiple, individually produced readings of the target area mosaism, quantitative, whole exome or genome sequencing	Limited in their ability to detect copy number variations, incidental findings need to be verified by sanger sequencing	Satam et al[41]
Targeted gene panels	Focused sequencing of disease-specific genes	Panel specific to GIST, IBD, hereditary colorectal cancer panel, gist panel	Accurate diagnosis focus on specific genes cost-effective and efficient: Can be customized according to disorder	Limited coverage not detect structural rearrangements or copy number variants cannot identify novel or new gene related to disease	Málaga et al[42]
Whole exome sequencing	All coding regions	Early-onset or monogenic IBD, congenital diarrheal disorders (e.g., DGAT1, EPCAM mutations). Hereditary pancreatitis (e.g., PRSS1, SPINK1) colorectal cancer	Cost-effective WES allows deeper sequencies WES captures approximately 85% of known disease-causing mutations	Misses non-coding variants incomplete exome coverage	Rabbani et al[43]; Uhlig et a[[44]
WGS	Coding and non-coding genome variant	Identification of colorectal cancer genes. Undiagnosed complex disease	Cover both coding and non-coding reason detection of structural variant both germline and somatic mutation	High cost difficult to pathogenic variant from benign variant	de Voer et al[45]
MLPA	Large deletions/duplications	Detects large deletions, especially EPCAM deletions causing MSH2 inactivation	Efficient CNV detection cost-effective and high throughput applicable on degraded DNA	Cannot detect point mutations or small indels limited to pre-designed probes	Kuiper et al[46]; Schouten et al[47]
qPCR	Copy number variations or known mutations	Rapid screening for common mutations, detects bacterial, viral, and parasitic DNA/RNA rapidly and accurately, bacterial load determination in gastro intestinal disorder	High sensitivity and specificity, rapid turnaround, quantitative	Requires prior sequence knowledge	Shah et al[48]; Bamias et al[49]
Array comparative genomic hybridization (aCGH)	Sub microscopic deletions/duplications, germline CNVs in genes like APC, SMAD4, and BMPR1A	Genome-wide coverage, germline CNVs in genes like APC, SMAD4 and BMPR1A	High resolution can detect CNVs as small as 50-100 kb	Inability to detect balanced chromosomal rearrangements difficulties in interpreting CNVs of uncertain significance	McKay et al[50]; Assämäki et al[51]
HLA typing (PCR-SSP, NGS-based)	HLA allele identification	Celiac disease, IBD pharmacogenetics IBD, primary sclerosing cholangitis drug-induced GI injury, idiosyncratic reactions to drugs causing hepatic/GI damage. Transplant compatibility	Cost-effective, simple requires minimal computational support	Limited resolution may not differentiate similar alleles. May yield ambiguous results	Megiorni and Pizzuti[52]
FISH	Large chromosomal rearrangements, gene fusions	In Barretts esophagus identifies chromosomal instability (e.g., 20q gain, 18q loss), and BRAF rearrangements; detection of HER2 gene amplification (ERBB2 at 17q12) predicts response to trastuzumab therapy (gastric cancer)	High specificity and sensitivity for targeted chromosomal regions	Targeted approach only. Limited genomic coverage	Brankley et al[53]
PCR	Specific known mutations	Quick detection (e.g., PRSS1 in hereditary pancreatitis), KRAS in CRC	High sensitivity and specificity can detect minute amounts of target DNA/RNA. Rapid turnaround time. Typically, within a few hours. Quantitative provides absolute or relative quantification	Requires prior sequence knowledge. Primers must be designed for specific known targets. Cannot differentiate live from dead organisms, detects DNA from both	Tol et al[54]
RNA-seq	Gene expression, fusion transcripts	Detects tumor-specific expression changes, fusion transcripts (e.g., NTRK fusions), and provides prognostic biomarkers in CRC reveals deregulated pathways (e.g., WNT, PI3K), tumor microenvironment features, and therapeutic target molecular marker of pancreatic cancer	Unbiased and comprehensive: Captures all RNA species (mRNA, lncRNA, miRNA, circular RNA), high resolution. Detects single-nucleotide changes, splicing variants, and gene fusions	Expensive and resource-intensive, requires advanced sequencing and computational infrastructure, data analysis is complex, needs bioinformatics expertise and robust pipelines	Bailey et al[55]

GI: Gastrointestinal; FISH: Fluorescence in situ hybridization; CNV: Copy number variation; aCGH: Array comparative genomic hybridization; SNP: Single nucleotide polymorphism; VUS: Variant of uncertain significance; SNV: Single nucleotide variant; NGS: Next-generation sequencing; GIST: Gastrointestinal stromal tumor; IBD: Inflammatory bowel disease; CRC: Colorectal cancer; WES: Whole exome sequencing; WGS: Whole genome sequencing; MLPA: Multiplex ligation-dependent probe amplification; qPCR: Quantitative polymerase chain reaction; HLA: Human leukocyte antigen; PCR-SSP: Polymerase chain reaction sequence-specific primer; NTRK: Neurotrophic tyrosine receptor kinase; PCR: Polymerase chain reaction; PI3K: Phosphoinositide 3-kinase; RNA-seq: RNA sequencing; lncRNA: Long non-coding RNA; miRNA: MicroRNA; mRNA: Messenger RNA.