Anemia Panel
Test code: HE0401
Is a 88 gene panel that includes assessment of non-coding variants.
Is ideal for patients suspected to have hereditary anemia who have had HBA1 and HBA2 variants excluded as the cause of their anemia or patients suspected to have hereditary anemia who are not suspected to have HBA1 or HBA2 variants as the cause of their anemia. The genes on this panel are included in the Comprehensive Hematology Panel.
Is not recommended for patients suspected to have anemia due to alpha-thalassemia (HBA1 or HBA2). These genes are highly homologous reducing mutation detection rate due to challenges in variant call and difficult to detect mutation profile (deletions and gene-fusions within the homologous genes tandem in the human genome).
Is not recommended for patients with a suspicion of severe Hemophilia A if the common inversions are not excluded by previous testing. An intron 22 inversion of the F8 gene is identified in 43%-45% individuals with severe hemophilia A and intron 1 inversion in 2%-5% (GeneReviews NBK1404; PMID:8275087, 8490618, 29296726, 27292088, 22282501, 11756167). This test does not detect reliably these inversions.
About Anemia
Anemia is defined as a decrease in the amount of red blood cells or hemoglobin in the blood. The symptoms of anemia include fatigue, weakness, pale skin, and shortness of breath. Other more serious symptoms may occur depending on the underlying cause. The causes of anemia may be classified as impaired red blood cell (RBC) production or increased RBC destruction (hemolytic anemias). Hereditary anemia may be clinically highly variable, including mild, moderate, or severe forms. Hb Bart syndrome is a severe form of anemia secondary to alpha thalassemia. It is characterized by hydrops fetalis leading to death almost always in utero or shortly after birth. The thalassemias, sickle cell disease, and other hemoglobinopathies represent a major group of inherited disorders of hemoglobin synthesis (HBA1, HBA2, HBB). The thalassemias are among the most common genetic disorders worldwide, occurring more frequently in the Mediterranean region, the Indian subcontinent, Southeast Asia, and West Africa. Hereditary spherocytosis and hereditary elliptocytosis are examples of inherited hemolytic anemias. Hereditary spherocytosis is the most common congenital hemolytic anemia among Caucasians with an estimated prevalence ranging from 1:2,000 to 1:5,000.
Availability
4 weeks
Gene Set Description
Genes in the Anemia Panel and their clinical significance Gene Associated phenotypes Inheritance ClinVar HGMD
ABCB7 Anemia, sideroblastic, and spinocerebellar ataxia XL 8 9
ADAMTS13 Schulman-Upshaw syndrome, Thrombotic thrombocytopenic purpura, AR 30 183 familial
AK1 Adenylate kinase deficiency, hemolytic anemia due to AR 8 10
ALAS2 Anemia, sideroblastic, Protoporphyria, erythropoietic XL 27 103
AMN Megaloblastic anemia-1, Norwegian AR 29 34
ANK1 Spherocytosis AD/AR 20 105
https://blueprintgenetics.com/ ATM Breast cancer, Ataxia-Telangiectasia AD/AR 1047 1109
ATR Cutaneous telangiectasia and cancer syndrome, Seckel syndrome AD/AR 10 33
ATRX Carpenter-Waziri syndrome, Alpha-thalassemia/mental retardation XL 65 165 syndrome, Holmes-Gang syndrome, Juberg-Marsidi syndrome, Smith- Fineman-Myers syndrome, Mental retardation-hypotonic facies syndrome
BLM Bloom syndrome AR 152 119
BRCA2 Fanconi anemia, Medulloblastoma, Glioma susceptibility, Pancreatic AD/AR 3369 2659 cancer, Wilms tumor, Breast-ovarian cancer, familial
BRIP1 Fanconi anemia, Breast cancer AD/AR 238 189
C15ORF41 Congenital dyserythropoietic anemia AR 3 3
CDAN1 Anemia, dyserythropoietic congenital AR 12 61
CLCN7 Osteopetrosis AD/AR 15 98
CUBN* Megaloblastic anemia-1, Finnish AR 42 53
CYB5R3 Methemoglobinemia due to methemoglobin reductase deficiency AR 21 71
DHFR* Megaloblastic anemia due to dihydrofolate reductase deficiency AR 2 5
DNAJC21 Bone marrow failure syndrome 3 AR 5 11
DNASE2 Primary immunodeficiency 2
EFL1 Shwachman-Diamond syndrome 3 2
EPB42 Spherocytosis AR 8 17
ERCC4 Fanconi anemia, Xeroderma pigmentosum, XFE progeroid syndrome AR 13 70
FANCA Fanconi anemia AR 191 677
FANCB Fanconi anemia XL 11 21
FANCC Fanconi anemia AR 94 64
FANCD2* Fanconi anemia AR 21 61
FANCE Fanconi anemia AR 4 17
FANCF Fanconia anemia AR 7 16
FANCG Fanconi anemia AR 16 92
FANCI Fanconi anemia AR 13 45
FANCL Fanconi anemia AR 13 24
FANCM Fanconi anemia AR 6 50
G6PD Glucose-6-phosphate dehydrogenase deficiency XL 45 226
https://blueprintgenetics.com/ GATA1 Anemia, without thrombocytopenia, Thrombocytopenia with beta- XL 21 15 thalessemia,, Dyserythropoietic anemia with thrombocytopenia
GCLC Gamma-glutamylcysteine synthetase deficiency AR 2 7
GPI Hemolytic anemia, nonspherocytic due to glucose phosphate AR 11 41 isomerase deficiency
GSS Glutathione synthetase deficiency AR 8 38
HBA1* Alpha-thalassemia (Hemoglobin Bart syndrome), Alpha-thalassemia AR/Digenic 27 214 (Hemoglobin H disease)
HBA2*,# Alpha-thalassemia (Hemoglobin Bart syndrome), Alpha-thalassemia AR/Digenic 44 290 (Hemoglobin H disease)
HBB Sickle cell disease, Thalassemia-beta, dominant inclusion body, Other AD/AR/Digenic 242 865 Thalassemias/Hemoglobinopathies, Beta-thalassemia, Hereditary persistence of fetal hemogoblin
HFE Hemochromatosis AR/Digenic 11 56
KIF23 Anemia, dyserythropoietic congenital AD 1 3
KLF1 Anemia, dyserythropoietic congenital, Blood group, Lutheran AD/BG 16 45 inhibitor, Hereditary persistence of fetal hemoglobin
LPIN2 Majeed syndrome AR 12 14
MTR Methylmalonic acidemia AR 13 43
NBN Breast cancer, Nijmegen breakage syndrome AD/AR 188 97
NT5C3A Uridine 5-prime monophosphate hydrolase deficiency, hemolytic AR 10 28 anemia due to
PALB2 Fanconi anemia, Pancreatic cancer, Breast cancer AD/AR 495 406
PC Pyruvate carboxylase deficiency AR 32 41
PDHA1 Leigh syndrome, Pyruvate dehydrogenase E1-alpha deficiency XL 66 192
PDHX Pyruvate dehydrogenase E3-binding protein deficiency AR 14 22
PIEZO1 Dehydrated hereditary stomatocytosis, Lympehedema, hereditary III AD/AR 23 60
PKLR Pyruvate kinase deficiency, Elevation of red blood cell ATP levels, AD/AR 17 277 familial
PUS1 Mitochondrial myopathy and sideroblastic anemia AR 7 9
RAD51C Fanconi anemia, Breast-ovarian cancer, familial AD/AR 107 125
REN Hyperuricemic nephropathy, Hyperproreninemia, familial, Renal AD/AR 9 18 tubular dysgenesis
RHAG Overhydrated hereditary stomatocytosis, Anemia, hemolytic, Rh-null, AD/AR/BG 13 28 regulator type, Anemia, hemolytic,Rh-Mod type, RHAG blood group
RPL11 Diamond-Blackfan anemia AD 12 45
https://blueprintgenetics.com/ RPL15* Diamond-Blackfan anemia AD 2 2
RPL27 Diamond-Blackfan anemia 16 1 1
RPL31 Diamond-Blackfan anemia AD 2
RPL35A Diamond-Blackfan anemia AD 7 14
RPL5 Diamond-Blackfan anemia AD 19 77
RPS10 Diamond-Blackfan anemia AD 3 5
RPS19 Diamond-Blackfan anemia AD 23 172
RPS24 Diamond-Blackfan anemia AD 6 10
RPS26 Diamond-Blackfan anemia AD 10 33
RPS28 Diamond-Blackfan anemia 15 with mandibulofacial dysostosis AD 1 1
RPS29 Diamond-Blackfan anemia AD 4 4
RPS7 Diamond-Blackfan anemia AD 2 10
SBDS* Aplastic anemia, Shwachman-Diamond syndrome, Severe AR 19 90 spondylometaphyseal dysplasia
SEC23B Anemia, dyserythropoietic congenital AR 18 121
SLC11A2 Anemia, hypochromic microcytic, with iron overload AR 5 10
SLC19A2 Thiamine-responsive megaloblastic anemia syndrome AR 14 51
SLC25A38 Anemia, sideroblastic 2, pyridoxine-refractory AR 7 27
SLC4A1 Spherocytosis, Ovalcytosis, Renal tubular acidosis, distal, with AD/AR/BG 38 122 hemolytic anemia, Cryohydrocytosis, Acanthocytosis, Band 3 Memphis
SLX4 Fanconi anemia AR 18 72
SPTA1 Spherocytosis, Ellipsocytosis, Pyropoikilocytosis AD/AR 29 51
SPTB Spherocytosis, Anemia, neonatal hemolytic, Ellipsocytosis AD/AR 24 99
SRP54 Shwachman-Diamond syndrome AD 3
TCN2 Transcobalamin II deficiency AR 9 35
TF Atransferrinemia AR 8 17
THBD Thrombophilia due to thrombomodulin defect, Hemolytic uremic AD 5 28 syndrome, atypical
TMPRSS6 Iron-refractory iron deficiency anemia AR 13 102
TPI1 Triosephosphate isomerase deficiency AR 8 19
XRCC2 Hereditary breast cancer AD/AR 10 21
YARS2 Myopathy, lactic acidosis, and sideroblastic anemia AR 27 11
https://blueprintgenetics.com/ *Some regions of the gene are duplicated in the genome. Read more.
# The gene has suboptimal coverage (means <90% of the gene’s target nucleotides are covered at >20x with mapping quality score (MQ>20) reads), and/or the gene has exons listed under Test limitations section that are not included in the panel as they are not sufficiently covered with high quality sequence reads.
The sensitivity to detect variants may be limited in genes marked with an asterisk (*) or number sign (#). Due to possible limitations these genes may not be available as single gene tests.
Gene refers to the HGNC approved gene symbol; Inheritance refers to inheritance patterns such as autosomal dominant (AD), autosomal recessive (AR), mitochondrial (mi), X-linked (XL), X-linked dominant (XLD) and X-linked recessive (XLR); ClinVar refers to the number of variants in the gene classified as pathogenic or likely pathogenic in this database (ClinVar); HGMD refers to the number of variants with possible disease association in the gene listed in Human Gene Mutation Database (HGMD). The list of associated, gene specific phenotypes are generated from CGD or Mitomap databases.
Non-coding disease causing variants covered by the panel
Gene Genomic HGVS RefSeq RS-number location HG19
ALAS2 ChrX:55054634 c.-15-2186C>G NM_000032.4
ALAS2 ChrX:55054635 c.-15-2187T>C NM_000032.4
ALAS2 ChrX:55054636 c.-15-2188A>G NM_000032.4
ALAS2 ChrX:55057393 c.-34C>T NM_000032.4 rs780642606
ALAS2 ChrX:55057617 c.-258C>G NM_000032.4 rs140772352
AMN Chr14:103395424 c.514-34G>A NM_030943.3 rs144077391
AMN Chr14:103396444 c.1007-31_1006+34delCCTCGCCCCGCCGCG NM_030943.3 rs386834161
AMN Chr14:103396458 c.1007-29_1006+36delTCGCCCCGCCGCGGG NM_030943.3 rs386834162
ANK1 Chr8:41566510 c.1900-17G>A NM_001142446.1 rs786205243
ANK1 Chr8:41566511 c.1900-18C>A NM_001142446.1
ANK1 Chr8:41655127 c.-73_-72delTG NM_020476.2 rs786205242
ATM Chr11:108093770 c.-174A>G NM_000051.3
ATM Chr11:108094508 c.-31+595G>A NM_000051.3
ATM Chr11:108098321 c.-30-1G>T NM_000051.3 rs869312754
ATM Chr11:108138753 c.2639-384A>G NM_000051.3
ATM Chr11:108141209 c.2839-579_2839-576delAAGT NM_000051.3
ATM Chr11:108151710 c.3403-12T>A NM_000051.3 rs201370733
ATM Chr11:108158168 c.3994-159A>G NM_000051.3 rs864622543
ATM Chr11:108164028 c.4612-12A>G NM_000051.3
ATM Chr11:108179837 c.5763-1050A>G NM_000051.3 rs774925473
ATM Chr11:108214779 c.8418+681A>G NM_000051.3 rs748635985
https://blueprintgenetics.com/ BRCA2 Chr13:32889805 c.-40+1G>A NM_000059.3
BRCA2 Chr13:32890469 c.-39-89delC NM_000059.3
BRCA2 Chr13:32890556 c.-39-1_-39delGA NM_000059.3 rs758732038
BRCA2 Chr13:32890558 c.-39-1G>A NM_000059.3 rs1060499566
BRCA2 Chr13:32900222 c.426-12_426-8delGTTTT NM_000059.3 rs276174844
BRCA2 Chr13:32945079 c.8488-14A>G NM_000059.3
BRCA2 Chr13:32953872 c.8954-15T>G NM_000059.3
BRCA2 Chr13:32971007 c.9502-28A>G NM_000059.3 rs397508059
BRCA2 Chr13:32971023 c.9502-12T>G NM_000059.3 rs81002803
BRIP1 Chr17:59858864 c.1629-498A>T NM_032043.2
CLCN7 Chr16:1506057 c.916+57A>T NM_001287.5
CLCN7 Chr16:1507356 c.739-18G>A NM_001287.5 rs371893553
CUBN Chr10:17088532 c.3330-439C>G NM_001081.3 rs386833782
FANCA Chr16:89805127 c.4261-19_4261-12delACCTGCTC NM_000135.3
FANCA Chr16:89816056 c.3239+82T>G NM_000135.2
FANCA Chr16:89818822 c.2982-192A>G NM_000135.2
FANCA Chr16:89831215 c.2778+83C>G NM_000135.2 rs750997715
FANCA Chr16:89836111 c.2504+134A>G NM_000135.2
FANCA Chr16:89836805 c.2223-138A>G NM_000135.2
FANCA Chr16:89849346 c.1567-20A>G NM_000135.2 rs775154397
FANCA Chr16:89864654 c.893+920C>A NM_000135.2
FANCC Chr9:98011653 c.-78-2A>G NM_000136.2 rs587779898
FANCC Chr9:98079807 c.-79+1G>A NM_000136.2
FANCD2 Chr3:10083186 c.696-121C>G NM_033084.3
FANCD2 Chr3:10102127 c.1766+40T>G NM_033084.3
FANCD2 Chr3:10106024 c.1948-16T>G NM_033084.3
FANCI Chr15:89825208 c.1583+142C>T NM_001113378.1
FANCL Chr2:58433394 c.375-2033C>G NM_001114636.1
GATA1 ChrX:48649496 c.-19-2A>G NM_002049.3
GSS Chr20:33537864 c.129+1663A>G NM_000178.2
GSS Chr20:33543525 c.-9+5G>A NM_000178.2
HBA1 Chr16:227471 c.*63_*65delCCT NM_000558.3
https://blueprintgenetics.com/ HBA2 Chr16:223646 c.*47G>C NM_000517.4 rs4021971
HBA2 Chr16:223672 c.*74_*89delCCTTCCTGGTCTTTGA NM_000517.4 rs63750919
HBA2 Chr16:223690 c.*93_*94delAA NM_000517.4 rs63751268
HBA2 Chr16:223691 c.*92A>G NM_000517.4 rs63750067
HBA2 Chr16:223693 c.*94A>G NM_000517.4
HBA2 Chr16:223693 c.*94A>C NM_000517.4
HBA2 Chr16:223703 c.*104G>T NM_000517.4
HBB Chr11:5246696 c.*132C>A/T NM_000518.4
HBB Chr11:5246696 c.*132C>A NM_000518.4 rs1420779550
HBB Chr11:5246696 c.*132C>T NM_000518.4
HBB Chr11:5246699 c.*129T>C NM_000518.4
HBB Chr11:5246711 c.*115_*116delAA NM_000518.4 rs281864532
HBB Chr11:5246713 c.*110_*114delTAAAA NM_000518.4 rs606231219,rs35949130
HBB Chr11:5246715 c.*113A>G NM_000518.4 rs33985472
HBB Chr11:5246716 c.*112A>G/T NM_000518.4 rs63750954
HBB Chr11:5246716 c.*112A>T NM_000518.4
HBB Chr11:5246716 c.*112A>G NM_000518.4
HBB Chr11:5246716 c.*110_*111delTA NM_000518.4 rs63750205,rs281864905
HBB Chr11:5246717 c.*111A>G NM_000518.4 rs63751128
HBB Chr11:5246718 c.*110T>A/C NM_000518.4 rs33978907
HBB Chr11:5246718 c.*110T>G NM_000518.4
HBB Chr11:5246720 c.*108A>C/G NM_000518.4
HBB Chr11:5246720 c.*108A>C NM_000518.4
HBB Chr11:5246720 c.*108A>G NM_000518.4
HBB Chr11:5246722 c.*93_*105delATCTGGATTCTGC NM_000518.4 rs34171453
HBB Chr11:5246732 c.*96T>C NM_000518.4 rs34029390
HBB Chr11:5246754 c.*74A>G NM_000518.4 rs369101035
HBB Chr11:5246781 c.*47C>G NM_000518.4
HBB Chr11:5246796 c.*32A>C NM_000518.4
HBB Chr11:5246970 c.316-14T>G NM_000518.4 rs35703285
HBB Chr11:5247046 c.316-90A>G NM_000518.4 rs63750433
HBB Chr11:5247062 c.316-106C>G NM_000518.4 rs34690599
https://blueprintgenetics.com/ HBB Chr11:5247102 c.316-146T>G NM_000518.4 rs35328027
HBB Chr11:5247153 c.316-197C>T NM_000518.4 rs34451549
HBB Chr11:5247216 c.316-260T>C NM_000518.4
HBB Chr11:5247602 c.315+203_315+205delTCTinsCC NM_000518.4
HBB Chr11:5248044 c.93-15T>G NM_000518.4 rs35456885
HBB Chr11:5248050 c.93-21G>A NM_000518.4 rs35004220
HBB Chr11:5248050 c.93-22delT NM_000518.4
HBB Chr11:5248263 c.-12C>T NM_000518.4 rs113115948
HBB Chr11:5248269 c.-18C>G NM_000518.4 rs34135787
HBB Chr11:5248272 c.-21T>A NM_000518.4
HBB Chr11:5248280 c.-29G>A/T NM_000518.4 rs34704828
HBB Chr11:5248281 c.-31delC NM_000518.4
HBB Chr11:5248282 c.-31C>T NM_000518.4 rs63750628
HBB Chr11:5248291 c.-41delT NM_000518.4 rs35352549
HBB Chr11:5248294 c.-43C>T NM_000518.4
HBB Chr11:5248301 c.-50A>C NM_000518.4 rs34305195
HBB Chr11:5248301 c.-50A>G/T NM_000518.4
HBB Chr11:5248326 c.-75G>T NM_000518.4
HBB Chr11:5248326 c.-75G>C NM_000518.4 rs63750400
HBB Chr11:5248326 NM_000518.4 rs63750953
HBB Chr11:5248327 c.-76A>C NM_000518.4 rs281864525
HBB Chr11:5248328 c.-77A>G/T NM_000518.4
HBB Chr11:5248328 NM_000518.4
HBB Chr11:5248328 NM_000518.4
HBB Chr11:5248329 c.-78A>C/G NM_000518.4 rs33931746
HBB Chr11:5248329 NM_000518.4
HBB Chr11:5248329 NM_000518.4
HBB Chr11:5248330 c.-79A>G NM_000518.4 rs34598529
HBB Chr11:5248330 NM_000518.4 rs397509430
HBB Chr11:5248331 c.-80T>A/C NM_000518.4 rs33980857
HBB Chr11:5248331 NM_000518.4
HBB Chr11:5248331 NM_000518.4
https://blueprintgenetics.com/ HBB Chr11:5248332 c.-81A>C/G NM_000518.4 rs33981098
HBB Chr11:5248332 NM_000518.4
HBB Chr11:5248332 NM_000518.4
HBB Chr11:5248333 c.-82C>A/T NM_000518.4 rs34500389
HBB Chr11:5248333 NM_000518.4
HBB Chr11:5248333 NM_000518.4
HBB Chr11:5248342 c.-91A>C NM_000518.4
HBB Chr11:5248343 c.-92C>G NM_000518.4 rs397515291
HBB Chr11:5248351 c.-100G>A NM_000518.4 rs281864524
HBB Chr11:5248372 c.-121C>T NM_000518.4 rs281864518
HBB Chr11:5248373 NM_000518.4 rs1272414751
HBB Chr11:5248374 c.-123A>T NM_000518.4
HBB Chr11:5248377 c.-126C>A NM_000518.4
HBB Chr11:5248378 c.-127G>C NM_000518.4
HBB Chr11:5248384 NM_000518.4 rs72561473
HBB Chr11:5248387 c.-136C>A/G/T NM_000518.4 rs33994806
HBB Chr11:5248387 NM_000518.4
HBB Chr11:5248387 NM_000518.4
HBB Chr11:5248387 NM_000518.4
HBB Chr11:5248388 c.-137C>A/G/T NM_000518.4 rs33941377
HBB Chr11:5248388 NM_000518.4
HBB Chr11:5248388 NM_000518.4
HBB Chr11:5248388 NM_000518.4
HBB Chr11:5248389 c.-138C>A/T NM_000518.4 rs33944208
HBB Chr11:5248389 NM_000518.4
HBB Chr11:5248389 NM_000518.4
HBB Chr11:5248391 NM_000518.4 rs34999973
HBB Chr11:5248393 c.-142C>T NM_000518.4 rs34883338
HBB Chr11:5248394 c.-143C>G NM_000518.4 rs63751043
HBB Chr11:5248402 c.-151C>T NM_000518.4 rs63751208
HBB Chr11:5248402 NM_000518.4
HBB Chr11:5248403 c.-152C>A NM_000518.4
https://blueprintgenetics.com/ HBB Chr11:5248491 c.-240G>A NM_000518.4 rs753344875
HBB Chr11:5248524 c.-273T>C NM_000518.4 rs139703273
HFE Chr6:26087649 c.-20G>A NM_000410.3 rs138378000
KLF1 Chr19:12998078 c.-124T>C NM_006563.3
KLF1 Chr19:12998102 NM_006563.3 rs552824864
KLF1 Chr19:12998108 c.-154C>T NM_006563.3 rs372651309
MTR Chr1:236971838 c.340-166A>G NM_000254.2
MTR Chr1:236977232 c.609+1088G>A NM_000254.2 rs752526782
MTR Chr1:237057461 c.3205-196A>G NM_000254.2 rs544410324
PALB2 Chr16:23649285 c.109-12T>A NM_024675.3 rs774949203
PC Chr11:66620883 c.1369-29A>G NM_000920.3
PDHA1 ChrX:19371182 c.533-17_533-14delTGTT NM_001173454.1
PDHA1 ChrX:19372579 c.625-30G>A NM_001173454.1
PDHA1 ChrX:19373648 c.873+26G>A NM_001173454.1
PDHA1 ChrX:19377849 c.*79_*90dupAGTCAATGAAAT NM_001173454.1 rs606231192
PDHA1 ChrX:19377861 c.*79_*90dupAGTCAATGAAAT NM_001173454.1
PDHX Chr11:34988372 c.816+11C>G NM_003477.2
PKLR Chr1:155263185 c.1269+44C>T NM_000298.5
PKLR Chr1:155265208 c.507+20C>A NM_000298.5
PKLR Chr1:155271258 c.-72A>G NM_000298.5
PKLR Chr1:155271259 c.-73G>C NM_000298.5
PKLR Chr1:155271269 c.-83G>C NM_000298.5
PKLR Chr1:155271269 NM_000298.5 rs1460844860
REN Chr1:204129817 c.374-12_374-11delTCinsAG NM_000537.3
RPL31 Chr2:101618778 c.-1+1G>A NM_001098577.2
RPL5 Chr1:93300322 c.190-12_191dupCTCTTACTATAGAT NM_000969.3
RPS19 Chr19:42364214 c.-144_-141delTTTC NM_001022.3
RPS26 Chr12:56436176 c.4-25_4-14delTAACAGTTTTCC NM_001029.3
RPS7 Chr2:3622941 c.-19+1G>T NM_001011.3
RPS7 Chr2:3622942 c.-19+2T>C NM_001011.3
SEC23B Chr20:18488060 c.-571A>G NM_006363.4 rs559854357
SEC23B Chr20:18488615 c.-16A>G NM_006363.4
https://blueprintgenetics.com/ SEC23B Chr20:18491731 c.221+31A>G NM_006363.4
SEC23B Chr20:18491863 c.221+163A>G NM_006363.4 rs573898514
SEC23B Chr20:18492791 c.222-78C>T NM_006363.4 rs150393520
SEC23B Chr20:18526845 c.1743+168A>G NM_006363.4 rs111951711
SLC4A1 Chr17:42340296 c.-62G>A NM_000342.3 rs387906565
SPTA1 Chr1:158613314 c.4339-99C>T NM_003126.2 rs200830867
SPTA1 Chr1:158626459 c.2806-13T>G NM_003126.2
TCN2 Chr22:31011112 c.581-176A>T NM_000355.3
TCN2 Chr22:31011112 c.581-176A>G NM_000355.3 rs372866837
THBD Chr20:23030319 NM_000361.2
THBD Chr20:23030443 c.-302C>A NM_000361.2
Test Strengths
The strengths of this test include:
CAP accredited laboratory CLIA-certified personnel performing clinical testing in a CLIA-certified laboratory Powerful sequencing technologies, advanced target enrichment methods and precision bioinformatics pipelines ensure superior analytical performance Careful construction of clinically effective and scientifically justified gene panels Some of the panels include the whole mitochondrial genome (please see the Panel Content section) Our Nucleus online portal providing transparent and easy access to quality and performance data at the patient level Our publicly available analytic validation demonstrating complete details of test performance ~2,000 non-coding disease causing variants in our clinical grade NGS assay for panels (please see ‘Non-coding disease causing variants covered by this panel’ in the Panel Content section) Our rigorous variant classification scheme Our systematic clinical interpretation workflow using proprietary software enabling accurate and traceable processing of NGS data Our comprehensive clinical statements
Test Limitations
HBA1 and HBA2 genes have identical sequences at coding region and their mapping rely purely on differences at intronic/UTR regions. This reduces sensitivity for detecting variants in these region by using standard NGS diagnostics. However, Blueprint Genetics custom assay has good coverage (>20x) with improved mapping rates (mapping quality >40) within the target regions of these genes: HBA1 80.7% and HBA2 59.4%. Our validation showed high mean coverage of 604x for HBA1 gene and 463x for HBA2. We have been able to detect sequence variants and some of the known disease causing deletions using our assay but some limitations in sensitivity is expected to exist at the moment. Genes with suboptimal coverage in our assay are marked with number sign (#) and genes with partial, or whole gene, segmental duplications in the human genome are marked with an asterisk (*) if they overlap with the UCSC pseudogene regions. Gene is considered to have suboptimal coverage when >90% of the gene’s target nucleotides are not covered at >20x with mapping quality score (MQ>20) reads. The technology may have limited sensitivity to detect variants in genes marked with these symbols (please see the Panel content table above).
This test does not d etect the following:
https://blueprintgenetics.com/ Complex inversions Gene conversions Balanced translocations Some of the panels include the whole mitochondrial genome (please see the Panel Content section) Repeat expansion disorders unless specifically mentioned Non-coding variants deeper than ±20 base pairs from exon-intron boundary unless otherwise indicated (please see above Panel Content / non-coding variants covered by the panel).
This test may not reliably detect the following:
Low level mosaicism in nuclear genes (variant with a minor allele fraction of 14.6% is detected with 90% probability) Stretches of mononucleotide repeats Low level heteroplasmy in mtDNA (>90% are detected at 5% level) Indels larger than 50bp Single exon deletions or duplications Variants within pseudogene regions/duplicated segments Some disease causing variants present in mtDNA are not detectable from blood, thus post-mitotic tissue such as skeletal muscle may be required for establishing molecular diagnosis.
The sensitivity of this test may be reduced if DNA is extracted by a laboratory other than Blueprint Genetics.
For additional information, please refer to the Test performance section and see our Analytic Validation.
Test Performance
The genes on the panel have been carefully selected based on scientific literature, mutation databases and our experience.
Our panels are sectioned from our high-quality, clinical grade NGS assay. Please see our sequencing and detection performance table for details regarding our ability to detect different types of alterations (Table).
Assays have been validated for various sample types including EDTA-blood, isolated DNA (excluding from formalin fixed paraffin embedded tissue), saliva and dry blood spots (filter cards). These sample types were selected in order to maximize the likelihood for high-quality DNA yield. The diagnostic yield varies depending on the assay used, referring healthcare professional, hospital and country. Plus analysis increases the likelihood of finding a genetic diagnosis for your patient, as large deletions and duplications cannot be detected using sequence analysis alone. Blueprint Genetics’ Plus Analysis is a combination of both sequencing and deletion/duplication (copy number variant (CNV)) analysis.
The performance metrics listed below are from an initial validation performed at our main laboratory in Finland. The performance metrics of our laboratory in Seattle, WA, are equivalent.
Performance of Blueprint Genetics high-quality, clinical grade NGS sequencing assay for panels.
Sensitivity % (TP/(TP+FN) Specificity %
Single nucleotide variants 99.89% (99,153/99,266) >99.9999%
Insertions, deletions and indels by sequence analysis
1-10 bps 99.2% (7,745/7,806) >99.9999%
11-50 bps 99.13% (2,524/2,546) >99.9999%
Copy number variants (exon level dels/dups)
1 exon level deletion (heterozygous) 100% (20/20) NA
1 exon level deletion (homozygous) 100% (5/5) NA
https://blueprintgenetics.com/ 1 exon level deletion (het or homo) 100% (25/25) NA
2-7 exon level deletion (het or homo) 100% (44/44) NA
1-9 exon level duplication (het or homo) 75% (6/8) NA
Simulated CNV detection
5 exons level deletion/duplication 98.7% 100.00%
Microdeletion/-duplication sdrs (large CNVs, n=37))
Size range (0.1-47 Mb) 100% (25/25)
The performance presented above reached by Blueprint Genetics high-quality, clinical grade NGS sequencing assay with the following coverage metrics
Mean sequencing depth 143X
Nucleotides with >20x sequencing coverage (%) 99.86%
Performance of Blueprint Genetics Mitochondrial Sequencing Assay.
Sensitivity % Specificity %
ANALYTIC VALIDATION (NA samples; n=4)
Single nucleotide variants
Heteroplasmic (45-100%) 100.0% (50/50) 100.0%
Heteroplasmic (35-45%) 100.0% (87/87) 100.0%
Heteroplasmic (25-35%) 100.0% (73/73) 100.0%
Heteroplasmic (15-25%) 100.0% (77/77) 100.0%
Heteroplasmic (10-15%) 100.0% (74/74) 100.0%
Heteroplasmic (5-10%) 100.0% (3/3) 100.0%
Heteroplasmic (<5%) 50.0% (2/4) 100.0%
CLINICAL VALIDATION (n=76 samples)
All types
Single nucleotide variants n=2026 SNVs
Heteroplasmic (45-100%) 100.0% (1940/1940) 100.0%
Heteroplasmic (35-45%) 100.0% (4/4) 100.0%
Heteroplasmic (25-35%) 100.0% (3/3) 100.0%
Heteroplasmic (15-25%) 100.0% (3/3) 100.0%
https://blueprintgenetics.com/ Heteroplasmic (10-15%) 100.0% (9/9) 100.0%
Heteroplasmic (5-10%) 92.3% (12/13) 99.98%
Heteroplasmic (<5%) 88.9% (48/54) 99.93%
Insertions and deletions by sequence analysis n=40 indels
Heteroplasmic (45-100%) 1-10bp 100.0% (32/32) 100.0%
Heteroplasmic (5-45%) 1-10bp 100.0% (3/3) 100.0%
Heteroplasmic (<5%) 1-10bp 100.0% (5/5) 99,997%
SIMULATION DATA /(mitomap mutations)
Insertions, and deletions 1-24 bps by sequence analysis; n=17
Homoplasmic (100%) 1-24bp 100.0% (17/17) 99.98%
Heteroplasmic (50%) 100.0% (17/17) 99.99%
Heteroplasmic (25%) 100.0% (17/17) 100.0%
Heteroplasmic (20%) 100.0% (17/17) 100.0%
Heteroplasmic (15%) 100.0% (17/17) 100.0%
Heteroplasmic (10%) 94.1% (16/17) 100.0%
Heteroplasmic (5%) 94.1% (16/17) 100.0%
Copy number variants (separate artifical mutations; n=1500)
Homoplasmic (100%) 500 bp, 1kb, 5 kb 100.0% 100.0%
Heteroplasmic (50%) 500 bp, 1kb, 5 kb 100.0% 100.0%
Heteroplasmic (30%) 500 bp, 1kb, 5 kb 100.0% 100.0%
Heteroplasmic (20%) 500 bp, 1kb, 5 kb 99.7% 100.0%
Heteroplasmic (10%) 500 bp, 1kb, 5 kb 99.0% 100.0%
The performance presented above reached by following coverage metrics at assay level (n=66)
Mean of medians Median of medians
Mean sequencing depth MQ0 (clinical) 18224X 17366X
Nucleotides with >1000x MQ0 sequencing coverage (%) (clinical) 100%
rho zero cell line (=no mtDNA), mean sequencing depth 12X
Bioinformatics
The target region for each gene includes coding exons and ±20 base pairs from the exon-intron boundary. In addition, the panel includes non-coding variants if listed above (Non-coding variants covered by the panel). Some regions of the gene(s)
https://blueprintgenetics.com/ may be removed from the panel if specifically mentioned in the ‘Test limitations” section above. The sequencing data generated in our laboratory is analyzed with our proprietary data analysis and annotation pipeline, integrating state-of-the art algorithms and industry-standard software solutions. Incorporation of rigorous quality control steps throughout the workflow of the pipeline ensures the consistency, validity and accuracy of results. Our pipeline is streamlined to maximize sensitivity without sacrificing specificity. We have incorporated a number of reference population databases and mutation databases such as, but not limited, to 1000 Genomes Project, gnomAD, ClinVar and HGMD into our clinical interpretation software to make the process effective and efficient. For missense variants, in silico variant prediction tools such as SIFT, PolyPhen, MutationTaster are used to assist with variant classification. Through our online ordering and statement reporting system, Nucleus, the customer has an access to details of the analysis, including patient specific sequencing metrics, a gene level coverage plot and a list of regions with inadequate coverage if present. This reflects our mission to build fully transparent diagnostics where customers have easy access to crucial details of the analysis process.
Clinical Interpretation
We provide customers with the most comprehensive clinical report available on the market. Clinical interpretation requires a fundamental understanding of clinical genetics and genetic principles. At Blueprint Genetics, our PhD molecular geneticists, medical geneticists and clinical consultants prepare the clinical statement together by evaluating the identified variants in the context of the phenotypic information provided in the requisition form. Our goal is to provide clinically meaningful statements that are understandable for all medical professionals regardless of whether they have formal training in genetics.
Variant classification is the corner stone of clinical interpretation and resulting patient management decisions. Our classifications follow the ACMG guideline 2015.
The final step in the analysis of sequence variants is confirmation of variants classified as pathogenic or likely pathogenic using bi-directional Sanger sequencing. Variant(s) fulfilling the following criteria are not Sanger confirmed: the variant quality score is above the internal threshold for a true positive call, and visual check-up of the variant at IGV is in-line with the variant call. Reported variants of uncertain significance are confirmed with bi-directional Sanger sequencing only if the quality score is below our internally defined quality score for true positive call. Reported copy number variations with a size <10 exons are confirmed by orthogonal methods such as qPCR if the specific CNV has been seen less than three times at Blueprint Genetics.
Our clinical statement includes tables for sequencing and copy number variants that include basic variant information (genomic coordinates, HGVS nomenclature, zygosity, allele frequencies, in silico predictions, OMIM phenotypes and classification of the variant). In addition, the statement includes detailed descriptions of the variant, gene and phenotype(s) including the role of the specific gene in human disease, the mutation profile, information about the gene’s variation in population cohorts and detailed information about related phenotypes. We also provide links to the references used, congress abstracts and mutation variant databases used to help our customers further evaluate the reported findings if desired. The conclusion summarizes all of the existing information and provides our rationale for the classification of the variant.
Identification of pathogenic or likely pathogenic variants in dominant disorders or their combinations in different alleles in recessive disorders are considered molecular confirmation of the clinical diagnosis. In these cases, family member testing can be used for risk stratification within the family. In the case of variants of uncertain significance (VUS), we do not recommend family member risk stratification based on the VUS result. Furthermore, in the case of VUS, we do not recommend the use of genetic information in patient management or genetic counseling.
Our interpretation team analyzes millions of variants from thousands of individuals with rare diseases. Thus, our database, and our understanding of variants and related phenotypes, is growing by leaps and bounds. Our laboratory is therefore well positioned to re-classify previously reported variants as new information becomes available. If a variant previously reported by Blueprint Genetics is re-classified, our laboratory will issue a follow-up statement to the original ordering health care provider at no additional cost.
ICD Codes
Refer to the most current version of ICD-10-CM manual for a complete list of ICD-10 codes.
https://blueprintgenetics.com/ Sample Requirements
Blood (min. 1ml) in an EDTA tube Extracted DNA, min. 2 μg in TE buffer or equivalent Saliva (Please see Sample Requirements for accepted saliva kits)
Label the sample tube with your patient's name, date of birth and the date of sample collection.
We do not accept DNA samples isolated from formalin-fixed paraffin-embedded (FFPE) tissue. In addition, if the patient is affected with a hematological malignancy, DNA extracted from a non-hematological source (e.g. skin fibroblasts) is strongly recommended.
Please note that, in rare cases, mitochondrial genome (mtDNA) variants may not be detectable in blood or saliva in which case DNA extracted from post-mitotic tissue such as skeletal muscle may be a better option.
Read more about our sample requirements here.
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