Analisis Varian Missense dan Profil Ekspresi Gen Terkait Hipotiroidisme Menggunakan Pendekatan Bioinformatika
Keywords:
hipotiroidisme, SNP, GWAS Catalog, GTEx, Ensembi, SNPnexusAbstract
Hipotiroidisme merupakan gangguan endokrin yang dipengaruhi oleh faktor genetik, faktor lingkungan, dan karakteristik populasi. Penelitian ini bertujuan untuk mengidentifikasi serta mengevaluasi kandidat varian genetik terkait hipotiroidisme menggunakan pendekatan bioinformatika in silico. Data diperoleh dari NHGRI–EBI GWAS Catalog dan disaring berdasarkan nilai p < 1 × 10⁻⁸ serta penghapusan data duplikat. Profil ekspresi gen dievaluasi melalui GTEx Portal, sedangkan lokasi dan konsekuensi genomik diperiksa menggunakan Ensembl. Dampak fungsional terhadap protein dianalisis menggunakan SNPnexus dan PolyPhen-2. Penelusuran awal menghasilkan 3.280 data asosiasi varian. Setelah filtrasi, diperoleh 899 SNP, terdiri atas 560 varian intron, 133 varian intergenic, 89 varian tanpa konteks, 44 varian exon non-coding transcript, 25 kandidat varian missense, dan 48 varian dalam kategori lainnya. Evaluasi ulang menunjukkan bahwa 25 kandidat belum seluruhnya terkonfirmasi sebagai varian missense karena terdapat ketidaksesuaian antara beberapa rsID, nama gen hasil pemetaan, lokasi kromosom, dan konsekuensi varian. Analisis GTEx hanya memberikan gambaran deskriptif distribusi ekspresi gen, sedangkan SNPnexus dan PolyPhen-2 tidak menghasilkan skor prediksi. Temuan ini mendukung penggunaan bioinformatika sebagai skrining awal, tetapi masih memerlukan anotasi yang terstandar dan validasi lanjutan.
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