Through ClientSite you can filter variants and download your reports
Endocrinology
Pituitary and hypothalamus pathologies
- Hypopituitarism – Deficiency of multiple pituitary hormones and isolated GH [53 genes]
Ref.: S-202414260|Turnaround time (TAT) 25 days
- Idiopathic and syndromic hypogonadotropic hypogonadism [62 genes]
Ref.: S-202414283|Turnaround time (TAT) 25 days
- Diabetes insipidus of genetic cause [45 genes]
Ref.: S-202414281|Turnaround time (TAT) 25 days
- Isolated deficiency or insensitivity to GH and IGF1 deficiency [8 genes]
Ref.: S-202414280|Turnaround time (TAT) 25 days
- Deficiency of multiple pituitary hormones [11 genes]
Ref.: S-202414279|Turnaround time (TAT) 25 days
- Complete central precocious puberty [4 genes]
Ref.: S-202414282|Turnaround time (TAT) 25 days
Parathyroid pathology
- Hyperparathyroidism [24 genes]
Ref.: S-202212129|Turnaround time (TAT) 25 days
- Hypoparathyroidism [30 genes]
Ref.: S-202414285|Turnaround time (TAT) 25 days
- Pseudohypoparathyroidism and differential diagnosis [10 genes]
Ref.: S-202414286|Turnaround time (TAT) 25 days
- GNAS. MLPA analysis [1 gene]
Ref.: S-202008509|Turnaround time (TAT) 20 days
Adrenal gland disorders
- Primary adrenal insufficiency [50 genes]
Ref.: S-202414287|Turnaround time (TAT) 25 days
- Decreased sensitivity to corticosteroids [26 genes]
Ref.: S-202414320|Turnaround time (TAT) 25 days
- Cushing’s syndrome [28 genes]
Ref.: S-202414321|Turnaround time (TAT) 25 days
- Primary hyperaldosteronism and differential diagnosis [13 genes]
Ref.: S-202414322|Turnaround time (TAT) 25 days
- Congenital adrenal hyperplasia [7 genes]
Ref.: S-202414288|Turnaround time (TAT) 25 days
- Congenital adrenal hyperplasia due to 21-hydroxylase deficiency: CYP21A2 sequencing and detection of rearrangements [1 gene]
Ref.: S-202212411|Turnaround time (TAT) 25 days
- Congenital adrenal hyperplasia due to 11-beta hydroxylase deficiency. CYP11B1 gene complete sequencing and detection of CYP11B1/CYP11B2 chimera [1 gene]
Ref.: S-202414328|Turnaround time (TAT) 25 days
- Complete central precocious puberty [4 genes]
Ref.: S-202414282|Turnaround time (TAT) 25 days
Associated with recurrent consultation
- Short stature associated with growth disorders [89 genes]
Ref.: S-202109994|Turnaround time (TAT) 25 days
- Leri-weill dyschondrosteosis. SHOX. MLPA analysis [1 gene]
Ref.: S-202110052|Turnaround time (TAT) 20 days
- Russell-Silver syndrome. Analysis of the 11p15 region by MS-MLPA [1 gene]
Ref.: S-202008035|Turnaround time (TAT) 20 days
- Silver-Russell syndrome. Uniparental disomy of chromosome 7 by MS-MLPA [1 gene]
Ref.: S-202009942|Turnaround time (TAT) 20 days
- Temple Syndrome. Uniparental disomy of chromosome 14 by MS-MLPA [1 gene]
Ref.: S-202212081|Turnaround time (TAT) 20 days
Other disorders in endocrinology
- Hyperinsulinemic hypoglycemia [29 genes]
Ref.: S-202414327|Turnaround time (TAT) 25 days
- Multiple endocrine neoplasia syndromes and differential diagnosis [18 genes]
Ref.: S-202414326|Turnaround time (TAT) 25 days
- Complete central precocious puberty [1 gene]
Ref.: S-202414325|Turnaround time (TAT) 25 days
- McCune-Albright syndrome. GNAS. NextGeneDx. Detection of the mutation p.Arg201Cys/His and p.Gln227Leu by NGS [1 gene]
Ref.: S-202314051|Turnaround time (TAT) 25 days
Other services
Gene sequencing
Turnaround time (TAT): 25 working days
Service of sequencing and interpretation of individual genes. Depending on its size and the regions of interest, we can offer an approach based on Sanger sequencing or based on NGS (enrichment by amplicons or by hybridization probes). NGS-based approach enables detection of copy number variation (CNV)
NextGenDx® massive sequencing (NGS)
Turnaround time (TAT): 25 working days
Next Generation Sequencing (NGS), or massive sequencing, is a term used to describe a set of new technologies capable of performing massive DNA sequencing. This means that millions of small pieces of DNA can be sequenced at the same time, creating a huge amount of data. This data can reach up to gigabytes of information, which is the equivalent of 1 billion base pairs of DNA. By comparison, previous methods could sequence only one piece of DNA at a time, generating between 500 and 1,000 base pairs of DNA in a single reaction.
NextGenDx® It is indicated in cases where it is intended to analyze a certain group of specific genes with maximum diagnostic precision. Addressed to:
- Monogenic diseases or diseases associated with a few large genes.
- Multigenic or genetically heterogeneous diseases whose differential diagnosis is complex.
MLPA analysis
Turnaround time (TAT): 20 working days
Semi-quantitative and widely contrasted technique in molecular genetics laboratories, that allows the diagnosis of pathologies due to variation in the number of copies and, in some cases, to methylation alterations. There are many commercial kits for the study of individual genes, panels of genes related to certain pathologies or extensive chromosomal regions involved in microdeletion/microduplication syndromes. HIC offers MLPA services based on the MRC-Holland kits.
Array CGH
Turnaround time (TAT): 25 working days
It is also known as a molecular karyotype and its main advantage over the karyotype is its great sensitivity, allowing the detection of structural variations that go unnoticed in a karyotype. CGH-array technology makes it possible to analyze losses or gains of genetic material and unbalanced rearrangements in the complete genome of an individual.
The CGX Postnatal 180K is specially designed for genetic diagnosis. It has a medium resolution of 100 kb throughout the entire genome and a high resolution of 20 kb in the regions of interest of the genome (regions that present a direct association between copy number variation and some pathology or syndrome described).
The 37K prenatal array is specially designed for prenatal diagnosis to detect the presence of genetic and chromosomal alterations in a single test. Its resolution is 10 times greater than that of a conventional karyotype and 50 times greater in the critical regions of the main syndromes. Without substantially decreasing the resolution in the regions of interest, the GCX 37K presents a low coverage in the rest of the genome in order to minimize diagnostic uncertainty as much as possible.
Variant segregation / Family studies
Turnaround time (TAT): 15 working days
Studies of carriers of previously described variants in the family using Sanger sequencing.
For structural variants (rearrangement, copy-number variation [insertions, deletions and duplications], inversions, translocations, etc. consult in atencionalcliente@healthincode.com
In vitro analysis for splicing variants
The normal process of gene transcription allows for the correct removal of introns and the joining of exons (splicing process) in messenger RNA to generate a functional protein. Advances in genomics have made it possible to expand sequencing to non-coding regions far from the canonical regions that flank the exons. Variants that affect pre-mRNA splicing (spliceogenic variants) are considered to be the cause of the disease with an estimated frequency of 15-50%, depending on the pathology under study.
These variants can induce exon exclusion, activation of cryptic splicing sites, or total/partial retention of the intron, generating an anomalous reading pattern. Frequently, these reading pattern abnormalities result in a premature stop codon in the mRNA, which could be degraded at the cellular level or give rise to a truncated or aberrantly sequenced protein, resulting in a consequent loss of function.
Bioinformatics in silico prediction tools do not always define the degree of involvement of variants in splicing defects. Functional ex vivo studies with RNA make it possible to elucidate the impact of genetic variants on splicing and the underlying molecular mechanism, which results in greater knowledge that can be transferred to clinical diagnosis.
Gene sequencing
Turnaround time (TAT): 25 working days
Service of sequencing and interpretation of individual genes. Depending on its size and the regions of interest, we can offer an approach based on Sanger sequencing or based on NGS (enrichment by amplicons or by hybridization probes). NGS-based approach enables detection of copy number variation (CNV)
NextGenDx® massive sequencing (NGS)
Turnaround time (TAT): 25 working days
Next Generation Sequencing (NGS), or massive sequencing, is a term used to describe a set of new technologies capable of performing massive DNA sequencing. This means that millions of small pieces of DNA can be sequenced at the same time, creating a huge amount of data. This data can reach up to gigabytes of information, which is the equivalent of 1 billion base pairs of DNA. By comparison, previous methods could sequence only one piece of DNA at a time, generating between 500 and 1,000 base pairs of DNA in a single reaction.
NextGenDx® It is indicated in cases where it is intended to analyze a certain group of specific genes with maximum diagnostic precision. Addressed to:
- Monogenic diseases or diseases associated with a few large genes.
- Multigenic or genetically heterogeneous diseases whose differential diagnosis is complex.
MLPA analysis
Turnaround time (TAT): 20 working days
Semi-quantitative and widely contrasted technique in molecular genetics laboratories, that allows the diagnosis of pathologies due to variation in the number of copies and, in some cases, to methylation alterations. There are many commercial kits for the study of individual genes, panels of genes related to certain pathologies or extensive chromosomal regions involved in microdeletion/microduplication syndromes. HIC offers MLPA services based on the MRC-Holland kits.
Array CGH
Turnaround time (TAT): 25 working days
It is also known as a molecular karyotype and its main advantage over the karyotype is its great sensitivity, allowing the detection of structural variations that go unnoticed in a karyotype. CGH-array technology makes it possible to analyze losses or gains of genetic material and unbalanced rearrangements in the complete genome of an individual.
The CGX Postnatal 180K is specially designed for genetic diagnosis. It has a medium resolution of 100 kb throughout the entire genome and a high resolution of 20 kb in the regions of interest of the genome (regions that present a direct association between copy number variation and some pathology or syndrome described).
The 37K prenatal array is specially designed for prenatal diagnosis to detect the presence of genetic and chromosomal alterations in a single test. Its resolution is 10 times greater than that of a conventional karyotype and 50 times greater in the critical regions of the main syndromes. Without substantially decreasing the resolution in the regions of interest, the GCX 37K presents a low coverage in the rest of the genome in order to minimize diagnostic uncertainty as much as possible.
Variant segregation / Family studies
Turnaround time (TAT): 15 working days
Studies of carriers of previously described variants in the family using Sanger sequencing.
For structural variants (rearrangement, copy-number variation [insertions, deletions and duplications], inversions, translocations, etc. consult in atencionalcliente@healthincode.com
In vitro analysis for splicing variants
The normal process of gene transcription allows for the correct removal of introns and the joining of exons (splicing process) in messenger RNA to generate a functional protein. Advances in genomics have made it possible to expand sequencing to non-coding regions far from the canonical regions that flank the exons. Variants that affect pre-mRNA splicing (spliceogenic variants) are considered to be the cause of the disease with an estimated frequency of 15-50%, depending on the pathology under study.
These variants can induce exon exclusion, activation of cryptic splicing sites, or total/partial retention of the intron, generating an anomalous reading pattern. Frequently, these reading pattern abnormalities result in a premature stop codon in the mRNA, which could be degraded at the cellular level or give rise to a truncated or aberrantly sequenced protein, resulting in a consequent loss of function.
Bioinformatics in silico prediction tools do not always define the degree of involvement of variants in splicing defects. Functional ex vivo studies with RNA make it possible to elucidate the impact of genetic variants on splicing and the underlying molecular mechanism, which results in greater knowledge that can be transferred to clinical diagnosis.
1) Download & fill out
Please cover as many fields as possible in both documents
2) Sample collection
See sample types in the guidelines
3) Pack the sample
Please pack the sample in a way to prevent leakage
4) Send the sample & the request
Please schedule the delivery for Monday–Friday: 8am – 5pm
5) Result: the report
Via: e-mail and/or through the customer portal
Request information on endocrine diseases
"*" indicates required fields
Short stature associated with growth disorders – 89 genes
BMPR1B, ACAN, COL10A1, COL11A1, COL11A2, COL2A1, COL9A1, COL9A2, COL9A3, COMP, FBN1, HSPG2, MATN3, NPPC, DVL1, PTHLH, ROR2, WNT5A, IHH, PTH1R, NPR2, IGF2, FGFR3, GH1, GHR, GHRHR, HESX1, IGF1, IGF1R, LHX3, LHX4, OTX2, POU1F1, PROP1, CRP, APCS, SOX2, SOX3, STAT5B, BLM, ANKRD11, CREBBP, EP300, KDM6A, KMT2D, LARP7, SHOX, SOX9, PAPPA2, BTK, CUL7, OBSL1, CCDC8, ORC1, ORC4, ORC6, CDT1, CDC6, GMNN, CDC45, MCM5, SPRED1, HRAS, SOS1, BRAF, KRAS, MAP2K1, MRAS, NRAS, RAF1, RASA2, RIT1, RRAS2, SOS2, LZTR1, ATR, DNA2, LIG4, RBBP8, SMARCAL1, TRAIP, XRCC4, CDKN1C, PLAG1, HMGA2, IGFALS, PTPN11, NF1, PCNT
Disorders of sexual development – atypical genitalia – 78 genes
AKR1C2, AKR1C4, AMH, AMHR2, AR, ARX, ATF3, ATRX, BMP15, CBX2, CDKN1C, CHD7, CTU2, CUL4B, CYB5A, CYP11A1, CYP11B1, CYP17A1, CYP19A1, CYP21A2, DHCR7, DHH, DHX37, DMRT1, DMRT2, EFCAB6, EMX2, ESR1, ESR2, FANCA, FGFR2, FOXL2, FSHR, FTHL17, GATA4, HHAT, HOXA13, HSD17B3, HSD17B4, HSD3B2, INSL3, KDM5D, LHCGR, LHX9, MAMLD1, MAP3K1, MAP3K4, MYRF, NR0B1, , NR2F2, NR5A1, PBX1, POR, PPP1R12A, PPP2R3C, RPL10, RSPO1, RXFP2, SAMD9, SGPL1, SOX10, SOX3, SOX8, SOX9, SRD5A2, SRY, STAR, STARD8, TOE1, TSPYL1, USP9Y, WNT4, WT1, WWOX, ZFPM2, ZFX, ZFY, ZNRF3
Hypothyroidism (global panel) – 380 genes
ABCB11, ABCB4, ABCC6, ABCC8, ACP5, ADA, ADAMTSL1, ADAR, ADAT3, ADCY5, AFF4, AIP, AIRE, AKT1, ALG2, ALG8, ALMS1, ALX4, ANAPC1, APC, APC2, APOE, ARL6, ARL6IP6, ARNT2, ARVCF, ASH1L, ATP11A, ATP5F1A, ATP5F1D, ATP5F1E, ATP5MK, ATP6V1B2, ATP8B1, ATPAF2, B3GLCT, B4GALT1, BAP1, BAZ1B, BBIP1, BBS1, BBS10, BBS12, BBS2, BBS4, BBS5, BBS7, BBS9, BCOR, BICRA, BMP4, BMP6, BRAF, BTNL2, BUB1, BUB1B, BUB3, BUD23, C1QBP, CACNA1C, CASZ1, CBLB, CCDC47, CD55, CDH23, CDKN1B, CDKN1C, CDON, CEP19, CEP290, CEP57, CFAP418, CHD6, CHD7, CHD8, CLIP2, CLPB, COMT, CPE, CRELD1, CTNNB1, CTNS, CYP27A1, DACT1, DCLRE1C, DDB1, DDOST, DEAF1, DIO1, DISP1, DLL1, DMXL2, DNAH1, DNAJC19, DNAJC30, DNM1L, DUOX2, DUOXA2, DYRK1A, EIF2AK3, EIF4H, ELN, ENPP1, EXOSC2, EXT2, FANCI, FARSA, FDX2, FGF13, FGF8, FGFR1, FKBP6, FLCN, FLII, FMR1, FOXA2, FOXE1, FOXH1, FOXI1, FOXP1, FOXP3, FUCA1, FUT8, GABRD, GAS1, GATA6, GCH1, GLI2, GLI3, GLIS3, GNA11, GNAS, GNB1, GNE, GP1BB, GPR101, GPR161, GRIA1, GRIN2B, GRM7, GTF2I, GTF2IRD1, GTF2IRD2, GYG1, HBB, HDAC4, HESX1, HFE, HGD, HID1, HIRA, HLA-DRB1, HMGA2, HNF1B, HNRNPK, HPD, HSD17B3, HSPG2, IFIH1, IFNG, IFT172, IFT27, IFT74, IGF2, IGSF1, IL2RA, IL2RG, IL6ST, IL7R, IMPDH2, INSR, IPO8, IQSEC2, IRF4, IRS4, ITCH, IYD, JAK1, JMJD1C, KANSL1, KARS1, KAT6B, KATNIP, KCNAB2, KCNJ10, KCNJ11, KDM6A, KISS1R, KLF1, KMT2B, KMT2D, LEP, LEPR, LHX3, LHX4, LIFR, LIG4, LIMK1, LRBA, LRP4, LSM11, LUZP1, LZTFL1, MAGEL2, MARS1, MC2R, MCM8, MDM4, MEN1, METTL27, MKKS, MKS1, MLXIPL, MMP23B, MOGS, MPI, MRAP, MTTP, MYT1L, NCF1, NDN, NEXMIF, NF2, NFKB2, NIN, NKX2-1, NKX2-5, NNT, NODAL, NPHP1, NPHS1, NR1H4, NR4A2, NSD1, OCA2, OPA1, OTX2, PAX8, PCSK1, PDE4D, PDGFB, PDPN, PHF21A, PIEZO1, PIK3C2A, PIK3CA, PLAA, PLAAT3, PLAG1, PLAGL1, PLCH1, PLVAP, PMM2, PNPLA6, POLG, POLG2, POLR3GL, POMC, POU1F1, POU3F4, PPP1R15B, PRDM16, PRIM1, PRKAR1A, PRKCZ, PROKR2, PROP1, PTCH1, PTEN, PTRH2, RAG1, RAG2, RAI1, RBM28, RERE, RFC2, RNASEH2A, RNASEH2B, RNASEH2C, RNPC3, ROBO1, RPL10, RREB1, RRM2B, SAA1, SALL1, SAMHD1, SASH3, SCAPER, SCLT1, SCN4A, SDCCAG8, SEC24C, SECISBP2, SETBP1, SGPL1, SHH, SIM1, SIX3, SKI, SKIC2, SKIC3, SLC16A2, SLC25A36, SLC25A4, SLC26A4, SLC37A4, SLC5A5, SLC6A17, SLF2, SMARCB1, SMARCE1, SMC1A, SMO, SNRPN, SOX2, SOX3, SPEN, SPOP, SRD5A3, SRY, STAG2, STAR, STAT1, STAT3, STEAP3, STIL, STUB1, STX1A, SUFU, SUPT16H, SVBP, TANGO2, TBC1D24, TBCK, TBL1X, TBL2, TBX1, TERT, TF, TG, TGIF1, THRA, THRB, TIAM1, TMEM270, TMEM67, TOM1, TONSL, TPO, TRAF7, TRAPPC9, TREX1, TRH, TRHR, TRIM32, TRIP13, TRMT10A, TSC1, TSC2, TSHB, TSHR, TTC8, TWNK, TXNRD2, UBE4B, UBR1, UBR7, UFD1, VPS37D, WDPCP, WDR11, WDR4, WFS1, XRCC4, YRDC, YY1, ZBTB20, ZFP57, ZIC2
Congenital hypothyroidism – 54 genes
CHD7, DIO1, DUOX1, DUOX2, DUOXA2, EXOSC2, FGF8, FGFR1, FOXA2, FOXE1, GBP1, GLI2, GLIS3, GNAS, HESX1, IGSF1, IRS4, IYD, JAG1, KMT2D, LEPR, LHX3, LHX4, NFKB2, NKX2-1, NKX2-5, NNT, NTN1, OTX2, PAX8, PCSK1, PDE4D, POU1F1, PRKAR1A, PROKR2, PROP1, RNPC3, SECISBP2, SLC16A2, SLC26A4, SLC26A7, SLC5A5, SOX2, SOX3, TBL1X, TG, THRA, THRB, TPO, TRHR, TRPC4AP, TSHB, TSHR, TUBB1
Monogenic and syndromic obesity – 96 genes
ADCY3, ADRB3, AFF4, AGRP, ALMS1, ANOS1, ARL6, ASIP, ATRX, BBIP1, BBS1, BBS10, BBS12, BBS2, BBS4, BBS5, BBS7, BBS9, BDNF, BRD4, CARTPT, CCDC28B, CDH23, CELA2A, CEP164, CEP19, CEP290, CFAP418, CPE, CREBBP, DYRK1B, EHMT1, ENPP1, EP300, FBN3, FFAR4, FGF8, FGFR1, FTO, GHRL, GNAS, HDAC8, IFT172, IFT27, IFT74, INPP5E, INSIG2, KIDINS220, KSR2, LEP, LEPR, LZTFL1, MAGEL2, MC3R, MC4R, MKKS, MKRN3, MKS1, MRAP2, MYT1L, NDN, NIPBL, NPAP1, NPY, NR0B2, NTRK2, PAX6, PCSK1, PHF6, PHIP, POMC, PPARG, PROK2, PROKR2, RAB23, RAD21, RAI1, RPS6KA3, SCAPER, SCLT1, SDC3, SDCCAG8, SH2B1, SIM1, SMC1A, SMC3, SNRPN, TMEM67, TRIM32, TTC8, TUB, UCP2, UCP3, VPS13B, WDPCP, WT1
Idiopathic and syndromic hypogonadotropic hypogonadism – 62 genes
AMH, AMHR2, ANOS1, AXL, CCDC141, CHD7, CYP19A1, DCC, DMXL2, DUSP6, FEZF1, FGF17, FGF8, FGFR1, FLRT3, FSHB, GH1, GHR, GNRH1, GNRHR, HESX1, HS6ST1, IGF1, IGSF10, IL17RD, KISS1, KISS1R, KLB, LEP, LEPR, LHB, LHX3, LHX4, NDNF, NR0B1, NR5A1, NSMF, NTN1, OTUD4, PCSK1, PLXNA1, PNPLA6, POLR3A, POLR3B, PROK2, PROKR2, PROP1, RAB3GAP1, RNF216, SEMA3A, SEMA3E, SEMA7A, SOX10, SOX11, SOX2, SOX3, SPRY4, TAC3, TACR3, TBX3, TUBB3, WDR11
Hypopituitarism – Deficiency of multiple pituitary hormones and isolated GH – 53 genes
ARNT2, AVP, BMP4, BTK, CDON, CHD7, CRHR1, NR0B1, EIF2S3, FGF8, FGFR1, FOXA2, GH1, GHRHR, GLI2, GLI3, GNRHR, HESX1, IGSF1, ANOS1, KMT2A, KMT2D, LHB, LHX3, LHX4, NFKB2, NR5A1, OTX2, PAX6, PCSK1, PITX2, PNPLA6, POMC, POU1F1, PROKR2, PROP1, RAX, RNPC3, ROBO1, SHH, SIX3, SOX2, SOX3, TBC1D32, TBL1X, TBX19, TCF7L1, TGIF1, TRHR, TSHB, UBR1, WFS1, ZIC2
Hypergonadotropic hypogonadism – 17 genes
BMP15, BMPR1B, CYP17A1, CYP19A1, DHH, DHX37, DMRT1, FOXL2, FSHR, GATA4, LHCGR, NR0B1, NR5A1, SOHLH1,SOX9, SRY, STAR
Diabetes insipidus of genetic cause – 45 genes
AIRE, ALMS1, ALX3, AQP2, AQP4, ARHGAP4, ARL6, ARNT2, AVP, AVPR1A, AVPR2, BBS1, CCDC28B, CNOT1, CPS1, CRLS1, FGF8, FGFR1, GH1, GLI2, GNA11, CMKLR2, GPR161, HESX1, HID1, KMT2D, KRT18, MC2R, NPHP1, OXT, PCSK1, PLA2G6, RAX, ROBO1, SHH, SIX3, SLC12A1, STRADA, TGIF1, TP63, IFT56, UBB, VIPAS39, VPS33B, WFS1
Hyperparathyroidism – 24 genes
AP2S1, CASR ,CCDC134 ,CDC73, CDKN1B, CLDN10, CYP27B1, CYP2R1, GCM2, GNA11, IL6R, MAX, MEN1, PLEKHM1, PTH1R, RAC2, RET, SLC12A1, SLC30A9, SLC4A2, TCIRG1, TRPV6, VDR, ZFX
Hypoparathyroidism – 30 genes
AIRE, ATP7B, CASR, CHD7, CLDN16, FAM111A, GATA3, GATA6, GCM2, GNA11, GNAS, HADHA, HADHB, IRX5, KMT2D, MPV17, NKX2-5, NKX2-6, PTH, PTH1R, SLC20A2, SOX3, STX16, TBCE, TBX1, TBX2, TG, TRPM6, TSHR, WDR37
Primary adrenal insufficiency – 50 genes
AAAS, ABCD1, AIRE, CDKN1C, CYP11A1, CYP11B1, CYP17A1, DHCR7, GFER, HSD17B4, HSD3B2, LIPA, MC2R, MCM4, MRAP, MRPS7, NFKB2, NNT, NR0B1, NR3C1, NR3C2, NR5A1, PCSK1, PEX1, PEX10, PEX12, PEX13, PEX16, PEX2, PEX26, PEX3, PEX5, PEX6, POLE, POMC, POR, QRSL1, ROBO1, SCNN1A, SCNN1B, SCNN1G, SERPINA6, SGPL1, STAR, TBX19, TXNRD2,SAMD9,NDUFAF5,WNT4,ACOX1
Hyperinsulinemic hypoglycemia – 29 genes
ABCC8, ALG3, ALG6, CACNA1D, CDKN1B, CDKN1C, DNAJC3, EIF2S3, GCK, GLUD1, HADH, HK1, HNF1A, HNF4A, INS, INSR, KCNJ11, MAFA, MAGEL2, MEN1, MPI, NSD1, PMM2, SLC16A1, SLC25A36, STX5, TRMT10A, UCP2, YARS1
Decreased sensitivity to corticosteroids – 26 genes
ADD1, AGT, AGTR1, ATP1B1, CA12, CUL3, CYP11B2, CYP3A5, ECE1, GNB3, H6PD, HSD11B1, HSD11B2, KCNJ1, KLHL3, NOS3, NR3C1, NR3C2, PTGIS, RGS5, SCNN1A, SCNN1B, SCNN1G, SLC12A3, WNK1, WNK4
Cushing’s syndrome – 28 genes
AIP, APC, ARMC5, CABLES1, CDKN1B, CDKN1C, CREBBP, EP300, FH, GNAS, MAX, MEN1, NF1, PDE11A, PDE8B, PRKACA, PRKAR1A, RET, SDHA, SDHAF2, SDHB, SDHC, SDHD, TMEM127, TP53, TSC1, TSC2, VHL
Multiple endocrine neoplasia syndromes and differential diagnosis – 18 genes
AIP, CASR, CDC73, CDH23, CDKN1B, GCM2, GPR101, MAX, MEN1, NF1, RET, SDHA, SDHAF2, SDHB, SDHC, SDHD, TMEM127, VHL
Primary hyperaldosteronism and differential diagnosis – 13 genes
CACNA1D, CACNA1H, CACNA1S, CLCN2, CLCNKA, CLCNKB, KCNJ10, KCNJ16, KCNJ5, SCNN1A, SCNN1B, SCNN1G, SLC12A3
Isolated deficiency or insensitivity to GH and IGF1 deficiency – 8 genes
GH1, GHR, GHRHR, GHSR, IGF1, IGF1R, IGFALS, STAT5B
Pseudohypoparathyroidism and differential diagnosis – 10 genes
FAM111A, GNAS, HDAC4, HOXD13, PDE4D, PRKAR1A, PRMT7, PTHLH, STX16, TBCE
Deficiency of multiple pituitary hormones – 11 genes
HESX1, GLI2, LHX3, LHX4, OTX2, POU1F1, PROP1, RNPC3, ROBO1, SOX2, SOX3
Congenital adrenal hyperplasia – 7 genes
CYP11B1, CYP17A1, HSD3B2, POR, STAR, KCNJ5, PDE8B
Complete central precocious puberty – 4 genes
DLK1, KISS1, KISS1R, MKRN3
Complete central precocious puberty – 1 gen
AIRE
